Triple
T34064149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Tergat |
E873572
|
entity |
| Predicate | hasCompetedOnSurface |
P50583
|
FINISHED |
| Object | track |
—
|
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: track | Statement: [Paul Tergat, hasCompetedOnSurface, track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompetedOnSurface Context triple: [Paul Tergat, hasCompetedOnSurface, track]
-
A.
hasCourtSurface
Indicates that something (such as a court or playing area) possesses a specific type of surface.
-
B.
hasSportsSurface
Indicates that one entity (typically a sports facility or area) is characterized by or equipped with a particular type of sports surface.
-
C.
hasRaceSurface
chosen
Indicates that an event or activity takes place on, or is associated with, a specific type of race surface.
-
D.
inauguralSeasonAtCurrentSurface
Indicates the season in which the current playing surface was first used.
-
E.
servedOnCourtDuring
Indicates that an individual held a judicial position on a particular court during a specified time period.
- 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:52 a.m.