Triple
T17803027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont-Saint-Martin |
E444481
|
entity |
| Predicate | demonym |
P191
|
FINISHED |
| Object |
Ponteins
Ponteins are the inhabitants of Pont-Saint-Martin, a commune in the Aosta Valley region of northwestern Italy.
|
E1288326
|
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: Ponteins | Statement: [Pont-Saint-Martin, demonym, Ponteins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ponteins Context triple: [Pont-Saint-Martin, demonym, Ponteins]
-
A.
Ponts
Ponts is the common short name for École des Ponts et Chaussées, one of France’s oldest and most prestigious engineering schools specializing in civil engineering, transportation, and environmental sciences.
-
B.
Ponte
Ponte is a Spanish-language surname of Iberian origin borne by various notable figures, including members of the Bolívar family.
-
C.
Pulleine
Pulleine is an English surname historically associated with British military and public figures.
-
D.
Pileni
Pileni is a small Polynesian outlier island community in the Solomon Islands, known for its Polynesian culture and language despite being located within Melanesia.
-
E.
Punt
Punt was an ancient trading region, likely located along the Red Sea or Horn of Africa, famed in Egyptian records for its exports of incense, ebony, gold, and exotic animals.
- 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: Ponteins Triple: [Pont-Saint-Martin, demonym, Ponteins]
Generated description
Ponteins are the inhabitants of Pont-Saint-Martin, a commune in the Aosta Valley region of northwestern Italy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ponteins Target entity description: Ponteins are the inhabitants of Pont-Saint-Martin, a commune in the Aosta Valley region of northwestern Italy.
-
A.
Ponts
Ponts is the common short name for École des Ponts et Chaussées, one of France’s oldest and most prestigious engineering schools specializing in civil engineering, transportation, and environmental sciences.
-
B.
Ponte
Ponte is a Spanish-language surname of Iberian origin borne by various notable figures, including members of the Bolívar family.
-
C.
Pulleine
Pulleine is an English surname historically associated with British military and public figures.
-
D.
Pileni
Pileni is a small Polynesian outlier island community in the Solomon Islands, known for its Polynesian culture and language despite being located within Melanesia.
-
E.
Punt
Punt was an ancient trading region, likely located along the Red Sea or Horn of Africa, famed in Egyptian records for its exports of incense, ebony, gold, and exotic animals.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4880171608190be2088c7a387bfb7 |
completed | April 19, 2026, 7:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02f8429de481909fd0c906e49bacb7 |
completed | May 12, 2026, 9:52 a.m. |
| NEDg | Description generation | batch_6a02f8ca36588190a1d5de8494777d61 |
completed | May 12, 2026, 9:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02f9de0ae48190816002a5d32718a1 |
completed | May 12, 2026, 9:58 a.m. |
Created at: April 10, 2026, 10:13 a.m.