Triple
T38432864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margie Wright |
E903853
|
entity |
| Predicate | numberOfCareerWins |
P8292
|
FINISHED |
| Object | over 1,400 NCAA softball victories |
—
|
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: over 1,400 NCAA softball victories | Statement: [Margie Wright, numberOfCareerWins, over 1,400 NCAA softball victories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCareerWins Context triple: [Margie Wright, numberOfCareerWins, over 1,400 NCAA softball victories]
-
A.
finalCareerWinOf
Indicates that one entity is the final career victory achieved by another entity (e.g., a player, team, or competitor).
-
B.
careerWins
chosen
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
C.
careerManagerialWins
Indicates the total number of games or contests an individual has won in a managerial role over the course of their entire career.
-
D.
careerWinLossRecord
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
E.
totalNationalSeriesWins
Indicates the total number of national series competitions that an entity has won.
- 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_69f76e6a2024819081aa04f4932f89d2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.