Triple
T8319307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NOS4A2 |
E194787
|
entity |
| Predicate | adaptationSeasons |
P2652
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [NOS4A2, adaptationSeasons, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationSeasons Context triple: [NOS4A2, adaptationSeasons, 2]
-
A.
adaptationStar
Indicates that one work is an adaptation of another, with the subject being the adapted work and the object being the original source.
-
B.
numberOfSeasons
chosen
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
C.
adaptationOfPeriod
Indicates that one entity is an adaptation or reinterpretation of another entity from a specific historical or cultural period.
-
D.
adaptationIn
Indicates that something appears, is represented, or takes place within a particular adaptation of an original work.
-
E.
seasonOfTitle
Indicates that one entity is a specific season or installment within the series or title represented by the other entity.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f648e10819081ad1fed870b2b86 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.