Triple
T8303592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hôpital Saint-Louis |
E194404
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Saint Louis |
E249388
|
NE FINISHED |
How this triple was built (2 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 Louis | Statement: [Hôpital Saint-Louis, namedAfter, Saint Louis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint Louis Context triple: [Hôpital Saint-Louis, namedAfter, Saint Louis]
-
A.
Saint Louis
chosen
Saint Louis is the canonized 13th-century king of France renowned for his piety, participation in the Crusades, and role in strengthening the French monarchy.
-
B.
Paris, Missouri
Paris, Missouri is a small rural city that serves as the county seat of Monroe County in northeastern Missouri, United States.
-
C.
St. Louis metropolitan area
The St. Louis metropolitan area is a bi-state urban region centered on the city of St. Louis, spanning parts of Missouri and Illinois and serving as a major Midwestern hub for culture, education, and industry.
-
D.
Philadelphia, Missouri
Philadelphia, Missouri is a small unincorporated community located in Marion County in the northeastern part of the state.
-
E.
Place Saint-Louis
Place Saint-Louis is a historic medieval square in Metz, France, known for its arcaded houses and lively cafés.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e8b9f6081909100d1da8a078616 |
completed | March 31, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d02f2a6ca88190b3f234447feab6e3 |
completed | April 3, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:53 p.m.