Triple
T17825058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamera vs. Guiron |
E445092
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object |
planet Terra
Planet Terra is a fictional alien world featured as the primary setting in the 1969 Japanese kaiju film "Gamera vs. Guiron."
|
E1289383
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: planet Terra | Statement: [Gamera vs. Guiron, setting, planet Terra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: planet Terra Context triple: [Gamera vs. Guiron, setting, planet Terra]
-
A.
Terra
Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
-
B.
Terra
Terra is a fictional character best known as the troubled, earth-controlling teen superheroine from DC Comics' Teen Titans franchise.
-
C.
Terra
Terra is a character from the film "I, Frankenstein," depicted as a central figure within its dark, supernatural world of gargoyles and demons.
-
D.
Terra
Terra is the Earth-analog human homeworld that serves as a central setting and cultural reference point in Ursula K. Le Guin’s Hainish Cycle of science fiction works.
-
E.
Terra
Terra is a NASA Earth-observing satellite that carries instruments to monitor the planet’s atmosphere, land, and oceans for climate and environmental research.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: planet Terra Triple: [Gamera vs. Guiron, setting, planet Terra]
Generated description
Planet Terra is a fictional alien world featured as the primary setting in the 1969 Japanese kaiju film "Gamera vs. Guiron."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: planet Terra Target entity description: Planet Terra is a fictional alien world featured as the primary setting in the 1969 Japanese kaiju film "Gamera vs. Guiron."
-
A.
Terra
Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
-
B.
Terra
Terra is a character from the film "I, Frankenstein," depicted as a central figure within its dark, supernatural world of gargoyles and demons.
-
C.
Terra
Terra is a fictional character best known as the troubled, earth-controlling teen superheroine from DC Comics' Teen Titans franchise.
-
D.
Terra
Terra is the Earth-analog human homeworld that serves as a central setting and cultural reference point in Ursula K. Le Guin’s Hainish Cycle of science fiction works.
-
E.
Terra
Terra is a NASA Earth-observing satellite that carries instruments to monitor the planet’s atmosphere, land, and oceans for climate and environmental research.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48914226c819083edcc78e00b2d42 |
completed | April 19, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02ff6d07308190bcf6c959204f89a6 |
completed | May 12, 2026, 10:22 a.m. |
| NEDg | Description generation | batch_6a03003084fc8190b7272f7d2e0735d7 |
completed | May 12, 2026, 10:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0300e885e481909c76dfbac2fd1009 |
completed | May 12, 2026, 10:28 a.m. |
Created at: April 10, 2026, 10:15 a.m.