Triple
T1781368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 4 |
E39297
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Les Halles area |
E163761
|
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: Les Halles area | Statement: [Paris Métro Line 4, connects, Les Halles area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Halles area Context triple: [Paris Métro Line 4, connects, Les Halles area]
-
A.
Beaubourg neighborhood
chosen
The Beaubourg neighborhood is a lively area in central Paris known for its modern art, street life, and the iconic Centre Pompidou.
-
B.
La Croix-Rousse
La Croix-Rousse is a historic hilltop district in Lyon, France, known for its silk-weaving heritage, steep slopes, and distinctive village-like atmosphere.
-
C.
Old Quarter
The Old Quarter is Hanoi’s historic city center, famed for its narrow streets, traditional shophouses, and vibrant street life that reflect the capital’s centuries-old commercial and cultural heritage.
-
D.
Grand-Place
Grand-Place is the central historic square of Lille, France, renowned for its ornate Flemish architecture and vibrant civic life.
-
E.
Latin Quarter
The Latin Quarter is a historic Parisian neighborhood famed for its universities, student life, and lively cafés and bookshops.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64e22d6881909ba6ec120b320918 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada99f52a08190854109d152c22be0 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.