Triple
T26699247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pohang-class corvette |
E673104
|
entity |
| Predicate | PohangIs |
P161133
|
FINISHED |
| Object | a city in North Gyeongsang Province, South Korea |
—
|
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: a city in North Gyeongsang Province, South Korea | Statement: [Pohang-class corvette, PohangIs, a city in North Gyeongsang Province, South Korea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PohangIs Context triple: [Pohang-class corvette, PohangIs, a city in North Gyeongsang Province, South Korea]
-
A.
hangulProjectCountry
Indicates that a country is associated with or involved in a Hangul-related project.
-
B.
andraChansenCity
Indicates that a given city is the location where the "Andra Chansen" (Second Chance) round of a competition takes place.
-
C.
ichinomiya
Indicates a relationship where a location or institution holds the status of "Ichinomiya," the primary or highest-ranking Shinto shrine of a historical province.
-
D.
קיבל
Indicates that an entity received or was given something from another entity.
-
E.
isNamesakeHomeOf
Indicates that a place serves as the home or primary location associated with the person, entity, or concept for which it is named.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6177e2870819092bd441b95a21223 |
completed | May 2, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60f24ed608190bffe6c6084fc2f7a |
completed | May 2, 2026, 2:50 p.m. |
Created at: April 27, 2026, 3:30 a.m.