Triple
T19070304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spyridon Samaras |
E466772
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Tigra
Tigra is an opera by Greek composer Spyridon Samaras, known for its late-Romantic style and contribution to early 20th-century Greek musical theater.
|
E1357333
|
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: Tigra | Statement: [Spyridon Samaras, notableWork, Tigra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tigra Context triple: [Spyridon Samaras, notableWork, Tigra]
-
A.
Tigra
Tigra is a feline-themed Marvel Comics superheroine known for her enhanced agility, strength, and senses, as well as her long-standing membership in various Avengers teams.
-
B.
Tigerman
Tigerman is the surname of Stanley Tigerman, a notable American architect associated with postmodern design.
-
C.
Tigarah
Tigarah is a Japanese rapper and singer known for her eclectic blend of hip hop, baile funk, and electronic music.
-
D.
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
-
E.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
- 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: Tigra Triple: [Spyridon Samaras, notableWork, Tigra]
Generated description
Tigra is an opera by Greek composer Spyridon Samaras, known for its late-Romantic style and contribution to early 20th-century Greek musical theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tigra Target entity description: Tigra is an opera by Greek composer Spyridon Samaras, known for its late-Romantic style and contribution to early 20th-century Greek musical theater.
-
A.
Tigra
Tigra is a feline-themed Marvel Comics superheroine known for her enhanced agility, strength, and senses, as well as her long-standing membership in various Avengers teams.
-
B.
Tigerman
Tigerman is the surname of Stanley Tigerman, a notable American architect associated with postmodern design.
-
C.
Tigarah
Tigarah is a Japanese rapper and singer known for her eclectic blend of hip hop, baile funk, and electronic music.
-
D.
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
-
E.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19ea01c8190b9bb789da32f9a90 |
completed | April 20, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05d35ca6848190a6d6695f9156488d |
completed | May 14, 2026, 1:51 p.m. |
| NEDg | Description generation | batch_6a05d53fbdf481908f60131dd2fcb15d |
completed | May 14, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05d5a12d708190922eb39ce2b515f8 |
completed | May 14, 2026, 2:01 p.m. |
Created at: April 10, 2026, 12:04 p.m.