Triple
T19497830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Rangers–New York Yankees rivalry |
E487818
|
entity |
| Predicate | fanBaseContrast |
P136140
|
FINISHED |
| Object | large-market vs growing-market dynamic |
—
|
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: large-market vs growing-market dynamic | Statement: [Texas Rangers–New York Yankees rivalry, fanBaseContrast, large-market vs growing-market dynamic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fanBaseContrast Context triple: [Texas Rangers–New York Yankees rivalry, fanBaseContrast, large-market vs growing-market dynamic]
-
A.
fanBaseInteraction
Indicates interactions or engagements occurring between a fan base and the subject, such as communication, feedback, or participatory activities.
-
B.
fanBaseSize
Indicates the size or magnitude of the group of fans or supporters associated with an entity.
-
C.
fanBase
Indicates that one entity is the group of admirers or supporters devoted to another entity.
-
D.
fanBaseScope
Indicates the extent or range of people who are considered fans or followers of an entity.
-
E.
fanBaseOverlap
Indicates that two entities share a significant portion of their fans or audience in common.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e634924e24819085cd61ba33c84570 |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.