Triple
T2655283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmet Catch |
E54592
|
entity |
| Predicate | tyreeRole |
P5518
|
FINISHED |
| Object | special teams player and backup receiver |
—
|
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: special teams player and backup receiver | Statement: [Helmet Catch, tyreeRole, special teams player and backup receiver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tyreeRole Context triple: [Helmet Catch, tyreeRole, special teams player and backup receiver]
-
A.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
B.
musicalRole
Indicates the specific function or part an entity performs within a musical context, such as in a performance, composition, or ensemble.
-
C.
typeOfRole
chosen
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
D.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
-
E.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.