Triple
T8267013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Survive and Advance |
E193324
|
entity |
| Predicate | inSeriesPosition |
P6115
|
FINISHED |
| Object | 30 for 30 documentary within the ESPN franchise |
—
|
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: 30 for 30 documentary within the ESPN franchise | Statement: [Survive and Advance, inSeriesPosition, 30 for 30 documentary within the ESPN franchise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inSeriesPosition Context triple: [Survive and Advance, inSeriesPosition, 30 for 30 documentary within the ESPN franchise]
-
A.
hasPartOfSeriesPosition
Indicates that an entity occupies a specific position or order within a larger series or sequence.
-
B.
episodeNumberInSeries
Indicates the specific sequential position an episode occupies within its overall series.
-
C.
positionInSeason
Indicates the specific ordinal placement or ranking of something within the sequence of items in a season.
-
D.
filmSeriesInstallmentNumber
Indicates the specific sequential position that a film occupies within a film series.
-
E.
placeInSeries
chosen
Indicates the position or order that something occupies within a sequence or series.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb794e6880819084dff5df42332835 |
completed | March 31, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69cb36b8707881909aca349230495a5a |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:50 p.m.