Triple
T29366349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish mayors |
E744727
|
entity |
| Predicate | notableExamplesInclude |
P100896
|
FINISHED |
| Object | mayor of Istanbul |
—
|
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: mayor of Istanbul | Statement: [Turkish mayors, notableExamplesInclude, mayor of Istanbul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableExamplesInclude Context triple: [Turkish mayors, notableExamplesInclude, mayor of Istanbul]
-
A.
notableExampleAt
Indicates that something serves as a prominent or illustrative example of something else in a particular context or location.
-
B.
notableExampleBy
Indicates that something serves as a prominent or illustrative example provided or created by a particular entity.
-
C.
includesExamplesSuchAs
chosen
Indicates that one entity provides specific instances or samples that illustrate or clarify another entity.
-
D.
notableUse
Indicates that something is prominently or famously used by a particular entity, context, or for a specific purpose.
-
E.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a0353887e848190ad98ecbbe7bbc061 |
completed | May 12, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_6a0352dfb5648190b9f8c9b7c388d2a1 |
completed | May 12, 2026, 4:18 p.m. |
Created at: April 28, 2026, 2:23 p.m.