Triple
T34458208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marques Haynes |
E884558
|
entity |
| Predicate | numberOfGamesPlayedWithHarlemGlobetrotters |
P205438
|
FINISHED |
| Object | over 12,000 |
—
|
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 12,000 | Statement: [Marques Haynes, numberOfGamesPlayedWithHarlemGlobetrotters, over 12,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGamesPlayedWithHarlemGlobetrotters Context triple: [Marques Haynes, numberOfGamesPlayedWithHarlemGlobetrotters, over 12,000]
-
A.
playedBasketballFor
Indicates that one entity was a member of and competed for another entity’s basketball team.
-
B.
NBACareerGames
Indicates the total number of games an individual has played over the course of their NBA career.
-
C.
playedInNBA
Indicates that the subject has participated as a player in at least one official National Basketball Association (NBA) game.
-
D.
hasNBAFranchiseHistoryFrom
Indicates that an entity has a history of operating an NBA franchise originating from a specified location or organization.
-
E.
NBAFinalsAppearances
Indicates the number of times an entity has participated in the NBA Finals series.
- 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2 a.m.