Triple
T37959627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Lady Boss |
E946969
|
entity |
| Predicate | isFilipinoFilm |
P189667
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [My Lady Boss, isFilipinoFilm, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFilipinoFilm Context triple: [My Lady Boss, isFilipinoFilm, true]
-
A.
isFromFilm
Indicates that something (such as a quote, character, scene, or element) originates from or appears in a particular film.
-
B.
isMotionPicture
Indicates that the subject is a motion picture (a film or movie work).
-
C.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
-
D.
hasTypeOfUseInFilm
Indicates that something is associated with a specific manner or category of use within the context of a film.
-
E.
isPreCodeFilm
Indicates that a film was produced and released before the enforcement of the Hollywood Production Code (Hays Code), and thus belongs to the pre-Code era.
- 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc7b6c2c88190ad4f58980834053c |
completed | May 6, 2026, 10:59 p.m. |
Created at: May 3, 2026, 4:20 p.m.