Triple
T2307713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Mets–Philadelphia Phillies rivalry |
E51878
|
entity |
| Predicate | fanTravelBetweenCities |
P9205
|
FINISHED |
| Object | common |
—
|
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: common | Statement: [New York Mets–Philadelphia Phillies rivalry, fanTravelBetweenCities, common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fanTravelBetweenCities Context triple: [New York Mets–Philadelphia Phillies rivalry, fanTravelBetweenCities, common]
-
A.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
B.
coTraveler
Indicates that two or more entities are traveling together along (part of) the same journey or route.
-
C.
involvedTravelBetween
chosen
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified locations.
-
D.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
E.
flightRoute
Indicates a path or sequence of locations that a particular flight travels between, typically from its origin to its destination (and possibly via intermediate stops).
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.