Triple
T288655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Jean King |
E5940
|
entity |
| Predicate | frenchOpenSinglesTitles |
P9290
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Billie Jean King, frenchOpenSinglesTitles, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frenchOpenSinglesTitles Context triple: [Billie Jean King, frenchOpenSinglesTitles, 1]
-
A.
playerCoachChampionshipYears
Indicates the years in which a specific coach led a particular player to win a championship.
-
B.
worldChampionshipDebut
Indicates the event or occasion on which an entity first appeared or participated in a world championship.
-
C.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
D.
finalsChampion
Indicates that an entity is the winner or champion of a particular final match, series, or tournament.
-
E.
pioneerOf
Indicates that an entity was among the first to develop, introduce, or significantly advance another entity, concept, or practice.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2f5c0081908e548b314f5e986d |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7c1448819082064f474633acd5 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.