Triple
T37363573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Mangiapane |
E927644
|
entity |
| Predicate | shootsAndCatches |
P127393
|
FINISHED |
| Object | left |
—
|
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: left | Statement: [Andrew Mangiapane, shootsAndCatches, left]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shootsAndCatches Context triple: [Andrew Mangiapane, shootsAndCatches, left]
-
A.
shootsCatches
Indicates that one entity shoots something that is then caught by another entity.
-
B.
shoots
Indicates that one entity propels a projectile or discharge toward another entity, typically with the intent to hit or affect it.
-
C.
playsShoots
chosen
Indicates that an entity participates in a sport or game using a particular shooting style or handedness (e.g., a hockey player who shoots left or right).
-
D.
shootsSide
Indicates that one entity fires a projectile or weapon toward the side of another entity, rather than directly at its front or back.
-
E.
shotIn
Indicates that an event, scene, or media production was filmed or recorded at a particular location.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8c38a9688190be524246f5682107 |
completed | May 6, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9c6e0481908565bd849e869b24 |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.