Triple
T34207560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 101 Marvellous Movies You May Have Missed |
E877554
|
entity |
| Predicate | numberOfWorksDiscussed |
P6221
|
FINISHED |
| Object | 101 |
—
|
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: 101 | Statement: [101 Marvellous Movies You May Have Missed, numberOfWorksDiscussed, 101]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorksDiscussed Context triple: [101 Marvellous Movies You May Have Missed, numberOfWorksDiscussed, 101]
-
A.
numberOfWorks
chosen
Indicates the total count of works associated with a given entity.
-
B.
notableWorkDiscussed
Indicates that a particular work (such as a book, film, or artwork) is the subject of discussion, analysis, or commentary in relation to another entity.
-
C.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
-
D.
approximateNumberOfWorks
Indicates an estimated or roughly calculated count of works associated with an entity.
-
E.
numberOfDialogues
Indicates the total count of dialogues associated with or occurring between the referenced entities.
- 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:55 a.m.