Triple
T28004674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronnie Simpson |
E707242
|
entity |
| Predicate | basedInCityDuringCelticCareer |
P183989
|
FINISHED |
| Object | Glasgow |
—
|
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: Glasgow | Statement: [Ronnie Simpson, basedInCityDuringCelticCareer, Glasgow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedInCityDuringCelticCareer Context triple: [Ronnie Simpson, basedInCityDuringCelticCareer, Glasgow]
-
A.
playedForCity
Indicates that an entity (typically a person or team) has been a member of or represented a sports team or organization based in a particular city.
-
B.
spentMostOfPlayingCareerWith
Indicates that an athlete spent the majority of their professional playing career with a particular team or organization.
-
C.
spentMostOfCareerIn
Indicates that an individual devoted the majority of their professional working life to being in or associated with a particular place, organization, or context.
-
D.
cityOfHomeStadium
Indicates the city in which a given home stadium is located.
-
E.
previousHomeGroundLocatedIn
Indicates that the location specified is where an entity’s former or earlier home ground was situated.
- 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_69ef96ba350c81908230d0b501b974c4 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 27, 2026, 7:59 p.m.