Triple
T288650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Jean King |
E5940
|
entity |
| Predicate | grandSlamDoublesTitles |
P9285
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Billie Jean King, grandSlamDoublesTitles, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandSlamDoublesTitles Context triple: [Billie Jean King, grandSlamDoublesTitles, 16]
-
A.
careerDoubles
Indicates the total number of doubles a person has achieved over the course of their entire career.
-
B.
mostOverallWinsRecord
Indicates that the subject holds the record for having the greatest total number of wins compared to all others in the relevant context.
-
C.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
D.
numberOfMarriages
Indicates the total count of times an entity has been legally married.
-
E.
wonWNBAChampionship
Indicates that an entity has achieved victory in the WNBA Finals and secured a WNBA championship title.
- 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.