Triple
T27303905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamphaeng Phet province |
E688996
|
entity |
| Predicate | hasAncientCityRuins |
P163458
|
FINISHED |
| Object | Kamphaeng Phet Historical Park |
—
|
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: Kamphaeng Phet Historical Park | Statement: [Kamphaeng Phet province, hasAncientCityRuins, Kamphaeng Phet Historical Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAncientCityRuins Context triple: [Kamphaeng Phet province, hasAncientCityRuins, Kamphaeng Phet Historical Park]
-
A.
hasRuinsOn
chosen
Indicates that one location or object contains or is the site of ruins situated upon it.
-
B.
ancientCity
Indicates that the subject is a historically old or long-established city, typically originating from ancient times.
-
C.
hasNearbyAncientCity
Indicates that one entity is located close to another entity that is classified as an ancient city.
-
D.
hasAncientCityState
Indicates that one entity possesses, contains, or is associated with an ancient city-state as part of its historical or geographical context.
-
E.
majorAncientCity
Indicates that a location functioned as a principal or highly significant city during ancient historical periods.
- 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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 27, 2026, 11:23 a.m.