Triple
T4353836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selma |
E98095
|
entity |
| Predicate | hasMediaPortrayal |
P50414
|
FINISHED |
| Object | depicted in the film "Selma" (2014) |
—
|
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: depicted in the film "Selma" (2014) | Statement: [Selma, hasMediaPortrayal, depicted in the film "Selma" (2014)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaPortrayal Context triple: [Selma, hasMediaPortrayal, depicted in the film "Selma" (2014)]
-
A.
mediaDepictionAs
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
B.
portrayedInFilmMedium
chosen
Indicates that an entity is depicted or represented within a film or cinematic work.
-
C.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
D.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
E.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c281688190aef717c4ecce8107 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:15 p.m.