Triple
T10197618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Michael Tyler |
E238802
|
entity |
| Predicate | numberOfEpisodesOnFriends |
P2593
|
FINISHED |
| Object | 150+ |
—
|
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: 150+ | Statement: [James Michael Tyler, numberOfEpisodesOnFriends, 150+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEpisodesOnFriends Context triple: [James Michael Tyler, numberOfEpisodesOnFriends, 150+]
-
A.
numberOfEpisodes
chosen
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
C.
episodeNumberInSeries
Indicates the specific sequential position an episode occupies within its overall series.
-
D.
episodeNumberInSeason
Indicates the specific sequential position an episode holds within a particular season of a series.
-
E.
downsPerSeries
Indicates the number of downs that occur within a single offensive series or possession.
- 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee3c44408190b09fa41f2d257c04 |
completed | April 2, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:13 p.m.