Triple
T32758731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Yong Yap |
E837697
|
entity |
| Predicate | locatedNearAdministrativeEntity |
P204066
|
FINISHED |
| Object | state of Perak |
—
|
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: state of Perak | Statement: [Mount Yong Yap, locatedNearAdministrativeEntity, state of Perak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedNearAdministrativeEntity Context triple: [Mount Yong Yap, locatedNearAdministrativeEntity, state of Perak]
-
A.
locatedNearRegion
Indicates that one entity is situated in close geographic proximity to a specified region.
-
B.
locatedNearCountry
Indicates that one entity is geographically situated close to the borders or territory of a specified country.
-
C.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
D.
locatedNearDistrict
Indicates that one entity is situated in close geographic proximity to a particular district.
-
E.
locatedNearSquare
Indicates that one entity is situated in close physical proximity to a square (such as a public plaza or open urban area).
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0316136a14819085bb88563d5abc42 |
completed | May 12, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_6a03158a962c81909f17d58197f6ba00 |
completed | May 12, 2026, 11:56 a.m. |
| PDg | Predicate description generation | batch_6a0316129c9081908f01528f62fe8997 |
completed | May 12, 2026, 11:59 a.m. |
Created at: May 1, 2026, 1:13 a.m.