Triple
T2677865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fielding Bible Award |
E56501
|
entity |
| Predicate | hasPanel |
P42161
|
FINISHED |
| Object | baseball analysts |
—
|
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: baseball analysts | Statement: [Fielding Bible Award, hasPanel, baseball analysts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPanel Context triple: [Fielding Bible Award, hasPanel, baseball analysts]
-
A.
hasPanelFormat
Indicates that something is associated with a particular panel layout or format used for its presentation or display.
-
B.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
C.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
D.
hasNumberOfVocationalPanels
Indicates the relationship specifying how many vocational panels are associated with a given entity.
-
E.
hasTab
Indicates that one entity includes, contains, or is associated with a tab element or tabbed section related 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda2dc5788190b4b83cb9ed08266c |
completed | March 7, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:54 p.m.