Triple
T11560726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TCC |
E274134
|
entity |
| Predicate | durationOfMostPrograms |
P24633
|
FINISHED |
| Object | two years |
—
|
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: two years | Statement: [TCC, durationOfMostPrograms, two years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationOfMostPrograms Context triple: [TCC, durationOfMostPrograms, two years]
-
A.
programLength
chosen
Indicates the duration or total length of a program, typically measured in time or size.
-
B.
longestDurationAt
Indicates that one entity has the greatest length of time associated with a particular state, event, or activity compared to other relevant entities.
-
C.
seriesLengthMaximum
Indicates the maximum allowable or observed length (e.g., number of items or installments) in a series.
-
D.
longRunningShow
Indicates that a show has been running for an extended period of time, typically across many episodes or seasons.
-
E.
maximumVideoLength
Indicates the greatest allowable or supported duration for a video in this context.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a899d4481909a3bce3147763b51 |
completed | April 10, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_69d85dc3fc2c8190bed7e2111301a77c |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:37 p.m.