Triple
T3874841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Havre AC |
E92474
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Le Havre |
E14638
|
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: Le Havre | Statement: [Le Havre AC, shortName, Le Havre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Havre Context triple: [Le Havre AC, shortName, Le Havre]
-
A.
Le Havre
chosen
Le Havre is a major French port city in Normandy, known as one of the country’s principal maritime and commercial gateways.
-
B.
The Lighthouse at Honfleur
The Lighthouse at Honfleur is an early pointillist seascape painting by Georges Seurat depicting the harbor and lighthouse of the French coastal town of Honfleur.
-
C.
Logorama
Logorama is a 2009 French animated short film that satirically depicts a world made entirely of corporate logos and mascots.
-
D.
Les Parisiens
Les Parisiens is the widely used French nickname for Paris Saint-Germain Football Club and its players, emphasizing their identity as representatives of Paris.
-
E.
Grande Illusions
Grande Illusions is a book by special effects artist Tom Savini that details his makeup and practical effects techniques used in horror and genre films.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec59bea08190b1e193f34944a2ee |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5124cdf588190b3b83ee8fb29450a |
completed | March 14, 2026, 7:46 a.m. |
Created at: March 9, 2026, 3:20 p.m.