Triple
T30362321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flora McKenzie Robson |
E772320
|
entity |
| Predicate | hasISNI |
P26132
|
FINISHED |
| Object | 0000 0001 2134 9470 |
—
|
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: 0000 0001 2134 9470 | Statement: [Flora McKenzie Robson, hasISNI, 0000 0001 2134 9470]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISNI Context triple: [Flora McKenzie Robson, hasISNI, 0000 0001 2134 9470]
-
A.
ISNI
chosen
Indicates that an entity is associated with a specific International Standard Name Identifier, uniquely identifying its public identity in creative or scholarly activities.
-
B.
hasORCID
Indicates that an entity is associated with a specific ORCID identifier, representing a unique researcher or contributor ID.
-
C.
hasDBLPAuthorId
Indicates that an entity is associated with a specific author identifier in the DBLP bibliographic database.
-
D.
hasAuthorAffiliationAtTimeOfPublication
Indicates that an author was affiliated with a particular organization or institution at the time a work was published.
-
E.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 7:58 p.m.