Triple
T16611830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Williams as Mork |
E403589
|
entity |
| Predicate | episodeCountApprox |
P45771
|
FINISHED |
| Object | 95 |
—
|
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: 95 | Statement: [Robin Williams as Mork, episodeCountApprox, 95]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: episodeCountApprox Context triple: [Robin Williams as Mork, episodeCountApprox, 95]
-
A.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
notableEpisodeCount
chosen
Indicates the number of episodes in which the subject is notably featured or recognized.
-
C.
hasEpisodeCountInFirstSeries
Indicates that an entity has a specific number of episodes in its first series or season.
-
D.
hasEpisodeCountPerSeries
Indicates a relationship where a series is associated with the number of episodes it contains.
-
E.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36096356c819092815d64db041793 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.