Triple
T35502502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Türkmenbaşy oil refinery |
E1026050
|
entity |
| Predicate | formerlyKnownAsCityNear |
P99823
|
FINISHED |
| Object | Krasnovodsk |
—
|
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: Krasnovodsk | Statement: [Türkmenbaşy oil refinery, formerlyKnownAsCityNear, Krasnovodsk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerlyKnownAsCityNear Context triple: [Türkmenbaşy oil refinery, formerlyKnownAsCityNear, Krasnovodsk]
-
A.
formerCityNameNearby
Indicates that an entity is located near a place that used to have a particular city name in the past.
-
B.
nearbyTownFormerName
chosen
Indicates that the nearby town previously had a different name, specifying its former name in relation to the current nearby town.
-
C.
formerNameOfRelatedCity
Indicates that one city previously had a different name that was historically used for another, related city.
-
D.
formerCityName
Indicates that an entity was previously known by a different city name in the past.
-
E.
locatedNearFormer
Indicates that one entity is situated close to another entity that previously occupied a nearby or the same location.
- 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_69f76dfc9c60819089c4217d93922615 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a005e8a2f7c819085bfc6f04b866d87 |
completed | May 10, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_6a005de82ef08190a015b385d1d3443c |
completed | May 10, 2026, 10:28 a.m. |
Created at: May 3, 2026, 4:04 p.m.