Triple
T37319892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Lamb Productions |
E926443
|
entity |
| Predicate | roleInPiecesOfAWoman |
P203776
|
FINISHED |
| Object | production company |
—
|
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: production company | Statement: [Little Lamb Productions, roleInPiecesOfAWoman, production company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInPiecesOfAWoman Context triple: [Little Lamb Productions, roleInPiecesOfAWoman, production company]
-
A.
femaleRole
Indicates that the role, function, or position involved is associated with or designated as female.
-
B.
roleInPatriarchalNarratives
Indicates how an entity functions within, reinforces, challenges, or is positioned by patriarchal storylines, structures, or discourses.
-
C.
sexualRole
Indicates the specific sexual function, position, or behavioral role one entity assumes in a sexual interaction or relationship with another.
-
D.
roleInTheWay
Indicates that one entity is obstructing, hindering, or otherwise blocking another entity’s progress, action, or intended path.
-
E.
roleInAtomicBlonde
Indicates that an entity has a specific role or participation in the film "Atomic Blonde."
- 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01f4d954e08190aff3756955212d67 |
completed | May 11, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_6a01edadb9248190be592287530740a5 |
completed | May 11, 2026, 2:54 p.m. |
| PDg | Predicate description generation | batch_6a01f4d84fa08190be6dea78f3fa9d8c |
completed | May 11, 2026, 3:25 p.m. |
Created at: May 3, 2026, 4:16 p.m.