Triple
T14795527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue Hoche |
E347765
|
entity |
| Predicate | hasNumberingEnd |
P38695
|
FINISHED |
| Object | Parc Monceau side |
—
|
LITERAL 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: Parc Monceau side | Statement: [Avenue Hoche, hasNumberingEnd, Parc Monceau side]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberingEnd Context triple: [Avenue Hoche, hasNumberingEnd, Parc Monceau side]
-
A.
hasEnd
chosen
Indicates that one entity serves as the terminal point, boundary, or conclusion of another entity or process.
-
B.
hasNumberingRole
Indicates that an entity holds a specific role or responsibility related to assigning, managing, or using numbers within a given context.
-
C.
hasEnding
Indicates that one entity concludes with, or terminates in, another entity (such as a specific substring, segment, or final component).
-
D.
numberingStatus
Indicates the status or condition of an entity’s assigned number or numbering process (e.g., whether it has been numbered, is pending, or has a particular numbering state).
-
E.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
- F. None of above.
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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.