Triple
T26513784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billabong Pro Tahiti |
E669757
|
entity |
| Predicate | heatFormat |
P160807
|
FINISHED |
| Object | man-on-man heats |
—
|
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: man-on-man heats | Statement: [Billabong Pro Tahiti, heatFormat, man-on-man heats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatFormat Context triple: [Billabong Pro Tahiti, heatFormat, man-on-man heats]
-
A.
degreeFormat
Indicates the specific way an academic degree is represented or formatted (e.g., abbreviation, style, or notation) in relation to an entity.
-
B.
heatSource
Indicates that one entity serves as a source of heat or heating for another entity.
-
C.
heatFlow
Indicates the transfer of thermal energy from one entity or region to another due to a temperature difference.
-
D.
thermalEffect
Indicates a relationship where one entity causes or experiences a change related to heat, such as temperature increase, decrease, or transfer, due to another entity or process.
-
E.
isHot
Indicates that an entity has a high temperature or is perceived as very warm.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61394b50c81909e628b2e5b1aa3d5 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f604120e848190b516c29b781d19cc |
completed | May 2, 2026, 2:02 p.m. |
Created at: April 27, 2026, 1:22 a.m.