Triple
T34417081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuk Young-soo |
E883426
|
entity |
| Predicate | officeHeldWithOrder |
P132400
|
FINISHED |
| Object | First Lady of South Korea, 3rd Republic |
—
|
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: First Lady of South Korea, 3rd Republic | Statement: [Yuk Young-soo, officeHeldWithOrder, First Lady of South Korea, 3rd Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldWithOrder Context triple: [Yuk Young-soo, officeHeldWithOrder, First Lady of South Korea, 3rd Republic]
-
A.
officeHeldUnder
Indicates that one entity holds or has held an official position, role, or office under the authority, jurisdiction, or administration of another entity.
-
B.
officeHeldOf
Indicates that a specific office or position is (or was) held by a particular person or entity.
-
C.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
D.
officeHeldIn
Indicates that a particular office or position is held within or associated with a specific geographic or administrative location.
-
E.
officeHeldWithNumber
chosen
Indicates that an entity holds a specific office or position together with an associated ordinal or numerical designation (e.g., first term, second office number).
- 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_69f349c2e3b88190a67834eb5bcffeaf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffb5c373948190a6606e8caa87a384 |
completed | May 9, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ffb261da788190b41399df8ed895e8 |
completed | May 9, 2026, 10:17 p.m. |
Created at: May 1, 2026, 1:59 a.m.