Triple
T1405865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muay Thai |
E31689
|
entity |
| Predicate | typicalNumberOfRounds |
P11575
|
FINISHED |
| Object | 5 rounds in professional bouts |
—
|
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: 5 rounds in professional bouts | Statement: [Muay Thai, typicalNumberOfRounds, 5 rounds in professional bouts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfRounds Context triple: [Muay Thai, typicalNumberOfRounds, 5 rounds in professional bouts]
-
A.
roundCount
chosen
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
B.
standardRoundLength
Indicates that there is a defined, typical duration assigned to a single round within a process, activity, or game.
-
C.
roundsFiredEstimate
Indicates an estimated number of shots or rounds that have been fired in a given context or event.
-
D.
hasProperRounds
Indicates that an entity is associated with rounds that meet specified standards or criteria for being considered proper or valid.
-
E.
typicalNumberOfSelections
Indicates the usual or expected count of selections made in a given choice or selection process.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bc55a08190a4dfe13a5378aff3 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.