Triple
T1187480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bibliothèque nationale de France |
E25279
|
entity |
| Predicate | GNDID |
P26133
|
FINISHED |
| Object | 2010273-0 |
—
|
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: 2010273-0 | Statement: [Bibliothèque nationale de France, GNDID, 2010273-0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GNDID Context triple: [Bibliothèque nationale de France, GNDID, 2010273-0]
-
A.
GNISID
Indicates that an entity is associated with a specific identifier from the U.S. Geographic Names Information System (GNIS), uniquely linking it to an official geographic feature record.
-
B.
identifierFor
Indicates that one entity serves as a unique identifying label or code for another entity.
-
C.
IDN
Indicates that two entities are identical in value, reference, or identity, representing exact sameness rather than mere similarity.
-
D.
identificationScope
Indicates the contextual boundary or extent within which an entity is uniquely identified or recognized.
-
E.
helpsIdentify
Indicates a relationship where one entity serves to distinguish, recognize, or determine the identity or characteristics of another entity.
- F. None of above. chosen
Provenance (4 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd5578b08190bbe4089857fbf166 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd0ab5f88190bb583fc63b4cc150 |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:45 p.m.