Triple
T28206039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Fisher |
E717023
|
entity |
| Predicate | primaryActivityInFilm |
P201602
|
FINISHED |
| Object | writing song lyrics |
—
|
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: writing song lyrics | Statement: [Sophie Fisher, primaryActivityInFilm, writing song lyrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryActivityInFilm Context triple: [Sophie Fisher, primaryActivityInFilm, writing song lyrics]
-
A.
primaryActor
Indicates that the referenced entity is the main participant or most central party responsible for the action or event in the relationship.
-
B.
primaryUsersInFilms
Indicates a relationship where certain users are the main or primary associated users for specific films.
-
C.
primaryCinema
Indicates that one entity is the main or most significant cinema associated with another entity (such as a person, work, or event).
-
D.
subjectOfFilm
Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
-
E.
primaryAspect
Indicates that one aspect is the main, most defining, or most emphasized characteristic or component of another entity or concept.
- 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_69efd6b826908190857e6e7dad74ed93 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a000be59ad88190a6aa3a42c097796d |
completed | May 10, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_6a000ab6e9bc81908300b81d004e5921 |
completed | May 10, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_6a000be4d3f48190bdecd0a044a0e453 |
completed | May 10, 2026, 4:39 a.m. |
Created at: April 27, 2026, 10:35 p.m.