Triple
T17735119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boulevard de Clichy |
E442692
|
entity |
| Predicate | hasNearbyDistrict |
P4647
|
FINISHED |
| Object | Pigalle |
—
|
NE NERFINISHED |
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: Pigalle | Statement: [Boulevard de Clichy, hasNearbyDistrict, Pigalle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pigalle Context triple: [Boulevard de Clichy, hasNearbyDistrict, Pigalle]
-
A.
Pigalle
chosen
Pigalle is a lively Parisian neighborhood known for its nightlife, cabarets, and proximity to Montmartre and the Moulin Rouge.
-
B.
Flandin
Flandin is a French surname most notably borne by Pierre-Étienne Flandin, a prominent 20th-century French politician and statesman.
-
C.
Renault–Gitane
Renault–Gitane was a dominant French professional cycling team of the late 1970s and early 1980s, known for nurturing multiple Grand Tour champions and pioneering modern team tactics.
-
D.
Arlois
Arlois are the inhabitants or natives of Arlay, sharing its cultural and regional identity.
-
E.
Monco
Monco is the laconic bounty hunter portrayed by Clint Eastwood in Sergio Leone’s Spaghetti Western "For a Few Dollars More."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478eaff6c81909c7bd438b8c6c987 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 10:08 a.m.