Triple
T28161428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ali Farokhmanesh |
E714905
|
entity |
| Predicate | madeShot |
P164082
|
FINISHED |
| Object | late three-point field goal vs. Kansas in 2010 NCAA Tournament |
—
|
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: late three-point field goal vs. Kansas in 2010 NCAA Tournament | Statement: [Ali Farokhmanesh, madeShot, late three-point field goal vs. Kansas in 2010 NCAA Tournament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: madeShot Context triple: [Ali Farokhmanesh, madeShot, late three-point field goal vs. Kansas in 2010 NCAA Tournament]
-
A.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
B.
shotFrom
Indicates that something is propelled or discharged starting at a particular source or origin.
-
C.
shotBy
Indicates that one entity fired a projectile or weapon that hit and wounded or killed another entity.
-
D.
shoots
Indicates that one entity propels a projectile or discharge toward another entity, typically with the intent to hit or affect it.
-
E.
shotDuring
Indicates that one event or action of shooting occurred within the temporal span of another specified event or time period.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f641eb9eec8190a50b58f0f28983b8 |
completed | May 2, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 27, 2026, 10:06 p.m.