Triple
T2594363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thrilla in Manila |
E58193
|
entity |
| Predicate | stoppageRound |
P15100
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Thrilla in Manila, stoppageRound, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stoppageRound Context triple: [Thrilla in Manila, stoppageRound, 14]
-
A.
stoppedAt
Indicates that an entity has come to a halt or pause at a specific location or point in time.
-
B.
majorStop
Indicates that a location functions as a primary or significant stop along a route or service path, typically where vehicles regularly halt for boarding, alighting, or key operations.
-
C.
hasStop
Indicates that something (such as a route, service, or journey) includes or is associated with a particular stop or stopping point.
-
D.
hasRound
chosen
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
-
E.
standardRoundLength
Indicates that there is a defined, typical duration assigned to a single round within a process, activity, or game.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd427f58c8190af1c1a9724158c96 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.