Triple
T15022710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Gaillard |
E378125
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Grand Andely
Grand Andely is a historic town in Normandy, France, known for its proximity to the medieval fortress Château Gaillard and its picturesque setting along the Seine River.
|
E1135782
|
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: Grand Andely | Statement: [Château Gaillard, locatedNear, Grand Andely]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grand Andely Context triple: [Château Gaillard, locatedNear, Grand Andely]
-
A.
Andilly
Andilly is a small commune in the Val-d'Oise department in the northern suburbs of Paris, France.
-
B.
Montbazon
Montbazon is a small commune in central France’s Indre-et-Loire department, known for its historic fortress and picturesque setting along the Indre River.
-
C.
Les Breuleux
Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
-
D.
Chavanges
Chavanges is a small commune in the Grand Est region of northeastern France, known for its rural character and traditional Champagne countryside setting.
-
E.
Assencières
Assencières is a small commune in the Aube department of north-central 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: Grand Andely Triple: [Château Gaillard, locatedNear, Grand Andely]
Generated description
Grand Andely is a historic town in Normandy, France, known for its proximity to the medieval fortress Château Gaillard and its picturesque setting along the Seine River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grand Andely Target entity description: Grand Andely is a historic town in Normandy, France, known for its proximity to the medieval fortress Château Gaillard and its picturesque setting along the Seine River.
-
A.
Andilly
Andilly is a small commune in the Val-d'Oise department in the northern suburbs of Paris, France.
-
B.
Montbazon
Montbazon is a small commune in central France’s Indre-et-Loire department, known for its historic fortress and picturesque setting along the Indre River.
-
C.
Les Breuleux
Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
-
D.
Chavanges
Chavanges is a small commune in the Grand Est region of northeastern France, known for its rural character and traditional Champagne countryside setting.
-
E.
Assencières
Assencières is a small commune in the Aube department of north-central 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded765462c819097f331c9b39c80e3 |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5b0bbf4819082e14715bfd6003d |
completed | May 9, 2026, 3:10 a.m. |
| NEDg | Description generation | batch_69fea6f926d481908cf4465205c628db |
completed | May 9, 2026, 3:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea9ab97e08190995c090c1fb9ed3b |
completed | May 9, 2026, 3:27 a.m. |
Created at: April 10, 2026, 2:56 a.m.