Triple
T24902695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATP Rankings |
E623621
|
entity |
| Predicate | highestPointsCategory |
P159044
|
FINISHED |
| Object | Grand Slam tournaments |
—
|
NE NERFINISHED |
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: Grand Slam tournaments | Statement: [ATP Rankings, highestPointsCategory, Grand Slam tournaments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestPointsCategory Context triple: [ATP Rankings, highestPointsCategory, Grand Slam tournaments]
-
A.
highestPointsForm
Indicates that a given form or configuration achieves the greatest number of points compared to all other relevant forms.
-
B.
hasHighestPoints
Indicates that the subject entity possesses the greatest number of points compared to all relevant others in the given context.
-
C.
highestCategory
Indicates that the related entity is the topmost or most specific category to which another entity is ultimately classified or assigned.
-
D.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
E.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 18, 2026, 5:27 a.m.