Triple
T15606800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantanhede |
E375178
|
entity |
| Predicate | hasParish |
P35
|
FINISHED |
| Object |
Lamas
Lamas is a civil parish in the municipality of Cantanhede in Portugal, known for its rural character and local cultural traditions.
|
E1166361
|
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: Lamas | Statement: [Cantanhede, hasParish, Lamas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lamas Context triple: [Cantanhede, hasParish, Lamas]
-
A.
Lamas
Lamas is a small historic city in Peru’s San Martín Region, known for its indigenous Quechua-speaking communities and traditional Amazonian-Andean culture.
-
B.
Tibbets
Tibbets is the surname of Paul W. Tibbets Jr., the American Air Force brigadier general who piloted the Enola Gay during the atomic bombing of Hiroshima in World War II.
-
C.
Phalba
Phalba is an unincorporated rural community located in Van Zandt County in northeastern Texas, United States.
-
D.
Pomburpa
Pomburpa is a village in the Indian state of Goa, known for its scenic riverside setting and traditional Goan culture.
-
E.
LAMA
LAMA is a light utility helicopter model, derived from the Aérospatiale SA 315 Lama, known for its high-altitude performance and use in mountain rescue and transport operations.
- 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: Lamas Triple: [Cantanhede, hasParish, Lamas]
Generated description
Lamas is a civil parish in the municipality of Cantanhede in Portugal, known for its rural character and local cultural traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lamas Target entity description: Lamas is a civil parish in the municipality of Cantanhede in Portugal, known for its rural character and local cultural traditions.
-
A.
Lamas
Lamas is a small historic city in Peru’s San Martín Region, known for its indigenous Quechua-speaking communities and traditional Amazonian-Andean culture.
-
B.
Tibbets
Tibbets is the surname of Paul W. Tibbets Jr., the American Air Force brigadier general who piloted the Enola Gay during the atomic bombing of Hiroshima in World War II.
-
C.
Phalba
Phalba is an unincorporated rural community located in Van Zandt County in northeastern Texas, United States.
-
D.
Pomburpa
Pomburpa is a village in the Indian state of Goa, known for its scenic riverside setting and traditional Goan culture.
-
E.
LAMA
LAMA is a light utility helicopter model, derived from the Aérospatiale SA 315 Lama, known for its high-altitude performance and use in mountain rescue and transport operations.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e7ec08c8190b3842cf3043aea27 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56d3541c8190a5a2aa9730260562 |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff578dc9dc8190ae0b1abcd74a6346 |
completed | May 9, 2026, 3:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff586ce89081909ebc1779bb9c4221 |
completed | May 9, 2026, 3:53 p.m. |
Created at: April 10, 2026, 4:13 a.m.