Triple
T29350404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Feet |
E744291
|
entity |
| Predicate | numberOfMainCouples |
P188763
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Cold Feet, numberOfMainCouples, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainCouples Context triple: [Cold Feet, numberOfMainCouples, 3]
-
A.
numberOfCentralCouples
chosen
Indicates the quantity of couples that occupy a central or primary position within a given context or structure.
-
B.
hasMainCouple
Indicates that a work or narrative features a primary romantic couple who are the central focus of its relationship storyline.
-
C.
numberOfMarriages
Indicates the total count of times an entity has been legally married.
-
D.
numberOfMainPerformers
Indicates the count of primary performers involved in a performance or event.
-
E.
maximumNumberOfKnightsAndLadies
Indicates the greatest allowable or observed count of entities classified as knights and ladies within a given context or scenario.
- 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_69f0a79a2d748190bc30abd469298b37 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69ffecdcbac4819093b725a7dbe0e61b |
completed | May 10, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69ffec3633288190adbbd84e277708dc |
completed | May 10, 2026, 2:23 a.m. |
Created at: April 28, 2026, 2:05 p.m.