Triple
T13012381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moret-sur-Loing |
E322450
|
entity |
| Predicate | hasCityGate |
P4365
|
FINISHED |
| Object |
Porte de Bourgogne
Porte de Bourgogne is a historic stone city gate in the medieval town of Moret-sur-Loing in north-central France.
|
E1015487
|
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: Porte de Bourgogne | Statement: [Moret-sur-Loing, hasCityGate, Porte de Bourgogne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porte de Bourgogne Context triple: [Moret-sur-Loing, hasCityGate, Porte de Bourgogne]
-
A.
Porte de Sens
Porte de Sens is a historic city gate in Villeneuve-sur-Yonne, France, notable as part of the town’s medieval fortifications.
-
B.
Porte de Loire
Porte de Loire is a tram stop on the Tours tramway network in the city of Tours, France.
-
C.
Porte Dauphine
Porte Dauphine is a Paris Métro station on Line 2, located near the Bois de Boulogne in the 16th arrondissement of Paris.
-
D.
Porte de Joigny
Porte de Joigny is a historic city gate in Villeneuve-sur-Yonne, France, notable as part of the town’s medieval fortifications.
-
E.
Porte de Strasbourg
Porte de Strasbourg is a historic city gate in Molsheim, France, notable as a preserved remnant of the town’s former fortifications.
- 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: Porte de Bourgogne Triple: [Moret-sur-Loing, hasCityGate, Porte de Bourgogne]
Generated description
Porte de Bourgogne is a historic stone city gate in the medieval town of Moret-sur-Loing in north-central France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Porte de Bourgogne Target entity description: Porte de Bourgogne is a historic stone city gate in the medieval town of Moret-sur-Loing in north-central France.
-
A.
Porte de Sens
Porte de Sens is a historic city gate in Villeneuve-sur-Yonne, France, notable as part of the town’s medieval fortifications.
-
B.
Porte de Loire
Porte de Loire is a tram stop on the Tours tramway network in the city of Tours, France.
-
C.
Porte Dauphine
Porte Dauphine is a Paris Métro station on Line 2, located near the Bois de Boulogne in the 16th arrondissement of Paris.
-
D.
Porte de Joigny
Porte de Joigny is a historic city gate in Villeneuve-sur-Yonne, France, notable as part of the town’s medieval fortifications.
-
E.
Porte de Strasbourg
Porte de Strasbourg is a historic city gate in Molsheim, France, notable as a preserved remnant of the town’s former fortifications.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecbb8f4819094d55eb07cb5ad97 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c10d5b9881909db688c1ab0e6a77 |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c277e6248190870b3bf9869716a7 |
completed | May 3, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c38bc0b08190b76cb0853d99ad82 |
completed | May 3, 2026, 3:39 a.m. |
Created at: April 9, 2026, 8:49 p.m.