Triple
T8720711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare de Saint-Pierre-des-Corps |
E207003
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Saint-Pierre-des-Corps
Saint-Pierre-des-Corps is a commune in central France, near Tours, known as a major railway hub on the Paris–Bordeaux high-speed line.
|
E776531
|
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: Saint-Pierre-des-Corps | Statement: [Gare de Saint-Pierre-des-Corps, locatedIn, Saint-Pierre-des-Corps]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Pierre-des-Corps Context triple: [Gare de Saint-Pierre-des-Corps, locatedIn, Saint-Pierre-des-Corps]
-
A.
Chapeauroux
Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
-
B.
Châteauroux
Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
-
C.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
D.
Pithiviers
Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
-
E.
Melun
Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
- 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: Saint-Pierre-des-Corps Triple: [Gare de Saint-Pierre-des-Corps, locatedIn, Saint-Pierre-des-Corps]
Generated description
Saint-Pierre-des-Corps is a commune in central France, near Tours, known as a major railway hub on the Paris–Bordeaux high-speed line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saint-Pierre-des-Corps Target entity description: Saint-Pierre-des-Corps is a commune in central France, near Tours, known as a major railway hub on the Paris–Bordeaux high-speed line.
-
A.
Chapeauroux
Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
-
B.
Châteauroux
Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
-
C.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
D.
Pithiviers
Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
-
E.
Melun
Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d03f0848190a50c77e5cd028ee7 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd5e548c8190898c01f9b8a27175 |
completed | April 3, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69d0013b50e081909595efe822bf5565 |
completed | April 3, 2026, 6:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d001f04db48190aaa1fb9efb36df2b |
completed | April 3, 2026, 6:07 p.m. |
Created at: March 30, 2026, 6:36 p.m.