Triple
T2008170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daddy Long Legs (1955 film) |
E43631
|
entity |
| Predicate | hasDanceSequences |
P35114
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Daddy Long Legs (1955 film), hasDanceSequences, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDanceSequences Context triple: [Daddy Long Legs (1955 film), hasDanceSequences, yes]
-
A.
hasDanceChoreography
Indicates that an entity is associated with or characterized by a specific dance choreography.
-
B.
hasDanceQuality
Indicates that something possesses a particular characteristic or attribute related to dance, such as style, skill, or expressive quality.
-
C.
choreographedIn
Indicates that an entity (typically a choreographer or group) created or arranged the choreography for a performance, work, or event in a specified context or production.
-
D.
hasTraditionalDance
Indicates that an entity is associated with, practices, or possesses a specific traditional dance.
-
E.
danceProp
Indicates that one entity is used or involved as a prop in another entity’s dance performance or dancing activity.
- F. None of above. chosen
Provenance (4 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb89aca908190b8b659af65afdf6f |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.