Triple
T3507060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NBA analyst for ESPN Radio |
E74100
|
entity |
| Predicate | mayWorkWith |
P398
|
FINISHED |
| Object | play-by-play announcer |
—
|
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: play-by-play announcer | Statement: [NBA analyst for ESPN Radio, mayWorkWith, play-by-play announcer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayWorkWith Context triple: [NBA analyst for ESPN Radio, mayWorkWith, play-by-play announcer]
-
A.
mayWorkIn
Indicates that an entity is allowed or has the possibility to work in a particular place, organization, or context.
-
B.
worksWith
chosen
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
C.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
D.
worksTo
Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
-
E.
worksThrough
Indicates that one entity performs an action, causes an effect, or achieves a result by using, employing, or acting via another entity as an intermediary or means.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbf52bd8819085a2ac5f48cc5c68 |
completed | March 8, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.