Triple
T20011492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamnet |
E494599
|
entity |
| Predicate | filmAdaptationAnnounced |
P138357
|
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: [Hamnet, filmAdaptationAnnounced, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmAdaptationAnnounced Context triple: [Hamnet, filmAdaptationAnnounced, true]
-
A.
filmAdaptationStarred
Indicates that a particular person played a starring role in a specific film adaptation of a work.
-
B.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
C.
filmAdaptationFormat
Indicates the specific medium or format (e.g., feature film, TV movie, short film) in which a work has been adapted into a film.
-
D.
filmAdaptationMusicBy
Indicates that the music for a film adaptation was composed or created by the specified person or entity.
-
E.
filmAdaptationGenre
Indicates that a film adaptation belongs to or is categorized under a particular genre.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623773d88190826616a02d3c3e69 |
completed | April 20, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:33 p.m.