Triple
T36988398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiz the Law |
E915026
|
entity |
| Predicate | TripleCrownRaceWon |
P187254
|
FINISHED |
| Object | Belmont Stakes |
—
|
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: Belmont Stakes | Statement: [Tiz the Law, TripleCrownRaceWon, Belmont Stakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TripleCrownRaceWon Context triple: [Tiz the Law, TripleCrownRaceWon, Belmont Stakes]
-
A.
tripleCrownWinner
Indicates that an entity has won all three major titles or championships that together constitute a "Triple Crown" within a particular sport or competitive domain.
-
B.
TripleCrownEligibility
Indicates that an entity meets all required conditions to be considered eligible to achieve the Triple Crown within a specified competitive context.
-
C.
tripleCrownYear
Indicates the year in which an entity achieved a Triple Crown title or completed a Triple Crown accomplishment.
-
D.
tripleCrownStatus
Indicates whether an entity has achieved, is pursuing, or holds a specific standing related to a recognized "triple crown" set of three major accomplishments or titles.
-
E.
previousTripleCrownWinner
Indicates that one entity is the Triple Crown winner who immediately preceded the other entity in time.
- 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_69f76e8dd0408190b8b46da118ea5128 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb34e4906c8190abb1c293fb84329a |
completed | May 6, 2026, 12:32 p.m. |
Created at: May 3, 2026, 4:14 p.m.