Triple
T30230666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Stars |
E768616
|
entity |
| Predicate | winLossRecordType |
P169004
|
FINISHED |
| Object | one of the best in USFL history |
—
|
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: one of the best in USFL history | Statement: [Philadelphia Stars, winLossRecordType, one of the best in USFL history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winLossRecordType Context triple: [Philadelphia Stars, winLossRecordType, one of the best in USFL history]
-
A.
careerWinLossRecord
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
B.
wonMatchType
Indicates that one entity achieved victory in a match of a specified type or category over another entity.
-
C.
winsFor
Indicates that one entity achieves victory or success on behalf of, or in favor of, another entity.
-
D.
seasonRecordWins
Indicates the number of games a team has won during a specific season.
-
E.
gamesLostBy
Indicates the number of games that one entity has been defeated in by 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_69f2248108208190be60bf1af343ce70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68025551081908f282e9ae3efebe7 |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 29, 2026, 7:36 p.m.