Triple
T19864650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1975 NBA Finals |
E477357
|
entity |
| Predicate | BulletsFranchiseFinalsAppearanceNumber |
P137623
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [1975 NBA Finals, BulletsFranchiseFinalsAppearanceNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BulletsFranchiseFinalsAppearanceNumber Context triple: [1975 NBA Finals, BulletsFranchiseFinalsAppearanceNumber, 2]
-
A.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
-
B.
numberOfGunmen
Indicates the quantity of individuals identified as gunmen involved in a particular event or situation.
-
C.
numberOfGuns
Indicates the quantity of guns associated with a given entity or situation.
-
D.
numberOfPeopleShot
Indicates the count of individuals who were shot in a particular event or context.
-
E.
shootsAgainst
Indicates that one entity fires a projectile or weapon in the direction of, or in opposition to, another entity.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589d55a88190af7d4e12c4b07739 |
completed | April 20, 2026, 4:47 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:51 p.m.