Triple
T109250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capital City Go-Go |
E2206
|
entity |
| Predicate | professional |
P5863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Capital City Go-Go, professional, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professional Context triple: [Capital City Go-Go, professional, true]
-
A.
practice
Indicates that an entity regularly performs an activity or skill, typically to improve proficiency or maintain competence.
-
B.
commercial
Indicates that one entity is engaged in a business-related or profit-oriented relationship, activity, or transaction with another entity.
-
C.
export
Indicates that one entity sends goods, services, or data out from its own domain or territory to another entity or external destination.
-
D.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
E.
employer
Indicates a relationship where one entity hires, pays, and oversees the work 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.