Triple
T33772291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESC 1991 |
E865410
|
entity |
| Predicate | pointsRunnerUp |
P87964
|
FINISHED |
| Object | 146 |
—
|
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: 146 | Statement: [ESC 1991, pointsRunnerUp, 146]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsRunnerUp Context triple: [ESC 1991, pointsRunnerUp, 146]
-
A.
runnersUpPoints
chosen
Indicates the number of points awarded to an entity for finishing as a runner-up in a competition or ranking.
-
B.
runnerUp
Indicates that one entity finished in second place relative to another in a competition or ranking.
-
C.
finishedRunnersUpIn
Indicates that one entity concluded a competition or contest in the runners-up position relative to another entity or event.
-
D.
runnerUpScore
Indicates the score achieved by the participant or entity that finished in second place in a competition or ranking.
-
E.
runnerUpRank
Indicates the position or ranking assigned to an entity that finishes immediately after the winner (or near the top) in a competition or ordered list.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:45 a.m.