Triple
T15044854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lascaux |
E379197
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Montignac
Montignac is a small town in southwestern France best known as the gateway to the prehistoric Lascaux cave complex.
|
E1141443
|
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: Montignac | Statement: [Lascaux, locatedNear, Montignac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montignac Context triple: [Lascaux, locatedNear, Montignac]
-
A.
Ribérac
Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
-
B.
Saint-Junien
Saint-Junien is a commune in west-central France known for its historical leather and glove-making industry and its location along the Vienne River.
-
C.
Figeac
Figeac is a historic town in southwestern France known for its medieval architecture and as the birthplace of Jean-François Champollion, who deciphered Egyptian hieroglyphs.
-
D.
Rochechouart
Rochechouart is a small historic town in west-central France known for its medieval château and proximity to the Rochechouart impact crater site.
-
E.
Guéret
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
- 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: Montignac Triple: [Lascaux, locatedNear, Montignac]
Generated description
Montignac is a small town in southwestern France best known as the gateway to the prehistoric Lascaux cave complex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Montignac Target entity description: Montignac is a small town in southwestern France best known as the gateway to the prehistoric Lascaux cave complex.
-
A.
Ribérac
Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
-
B.
Saint-Junien
Saint-Junien is a commune in west-central France known for its historical leather and glove-making industry and its location along the Vienne River.
-
C.
Figeac
Figeac is a historic town in southwestern France known for its medieval architecture and as the birthplace of Jean-François Champollion, who deciphered Egyptian hieroglyphs.
-
D.
Rochechouart
Rochechouart is a small historic town in west-central France known for its medieval château and proximity to the Rochechouart impact crater site.
-
E.
Guéret
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded830c3c08190a87b81abbbb75377 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec87725348190a0da7555b62adbdc |
completed | May 9, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_69fec9d32f388190aef036dde9cdda42 |
completed | May 9, 2026, 5:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feca4a9db08190a083b5f0d9ec091b |
completed | May 9, 2026, 5:46 a.m. |
Created at: April 10, 2026, 3 a.m.