Triple
T1459775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olson database |
E31483
|
entity |
| Predicate | primaryFile |
P29007
|
FINISHED |
| Object | zone.tab |
—
|
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: zone.tab | Statement: [Olson database, primaryFile, zone.tab]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFile Context triple: [Olson database, primaryFile, zone.tab]
-
A.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
B.
primaryReference
Indicates that one entity serves as the main or authoritative source of information or citation for another entity.
-
C.
primaryComponent
Indicates that one entity serves as the main or most important component within another entity or system.
-
D.
primaryType
Indicates the main or most fundamental category or classification assigned to an entity, distinguishing it from any secondary or auxiliary types.
-
E.
primaryName
Indicates that the associated name is the main or most commonly used name for the entity in question.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59d6dd88190b8ff3bda90aef7e2 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.