Triple
T15261095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sprinter Sacre |
E364775
|
entity |
| Predicate | careerRecord |
P18724
|
FINISHED |
| Object | 24 starts, 18 wins, 2 seconds, 1 third |
—
|
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: 24 starts, 18 wins, 2 seconds, 1 third | Statement: [Sprinter Sacre, careerRecord, 24 starts, 18 wins, 2 seconds, 1 third]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerRecord Context triple: [Sprinter Sacre, careerRecord, 24 starts, 18 wins, 2 seconds, 1 third]
-
A.
careerWinLossRecord
chosen
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
B.
careerRuns
Indicates the total number of runs a player has scored over the entire duration of their professional career.
-
C.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
D.
careerHits
Indicates the total number of hits a player has accumulated over the course of their entire professional career.
-
E.
careerSeasons
Indicates the number or set of seasons during which an entity actively participated in a particular career or professional role.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084e85a08190b8e63598b9f6a535 |
completed | April 15, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:14 a.m.