Triple
T36981664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongguan Leopards |
E914844
|
entity |
| Predicate | hasFivePlayersOnCourt |
P39863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dongguan Leopards, hasFivePlayersOnCourt, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFivePlayersOnCourt Context triple: [Dongguan Leopards, hasFivePlayersOnCourt, true]
-
A.
minimumNumberOnCourt
Indicates the smallest required number of participants that must be present on the court for play or a rule condition to be satisfied.
-
B.
usesNumberOfPlayersOnFieldPerTeam
chosen
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
-
C.
hasNumberOfTeamsOnFieldPerSide
Indicates the number of teams that are simultaneously present on the field on each opposing side in a game or sport.
-
D.
numberOfPlayersPerTeam
Indicates the quantity of players that are assigned to or allowed on each team in a given context.
-
E.
numberOfTeamsOnFieldPerSide
Indicates how many teams are present on the field for each opposing side during play.
- 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_69f76e8dd0408190b8b46da118ea5128 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: May 3, 2026, 4:14 p.m.