Triple
T180256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Taipei |
E3857
|
entity |
| Predicate | nameUsedToAvoid |
P6275
|
FINISHED |
| Object | explicit reference to Taiwan’s political status |
—
|
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: explicit reference to Taiwan’s political status | Statement: [Chinese Taipei, nameUsedToAvoid, explicit reference to Taiwan’s political status]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameUsedToAvoid Context triple: [Chinese Taipei, nameUsedToAvoid, explicit reference to Taiwan’s political status]
-
A.
nameUsedBy
Indicates that a particular name is employed or referenced by a specific entity.
-
B.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
C.
usedPseudonym
Indicates that an entity performed an action or participated in a context under a name that was not their real or primary identity.
-
D.
formerName
Indicates that an entity was previously known by a different name in the past.
-
E.
nameOf
Indicates that one entity is the name or designation of another entity.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25901a9188190b8f510bec8c8e7f2 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566ccc288190add5624ede96d82b |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575e7c7c819095167d8a862c255a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.