Triple
T32096803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flame of Udûn |
E819740
|
entity |
| Predicate | spokenInSceneWith |
P93257
|
FINISHED |
| Object | You cannot pass |
—
|
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: You cannot pass | Statement: [Flame of Udûn, spokenInSceneWith, You cannot pass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInSceneWith Context triple: [Flame of Udûn, spokenInSceneWith, You cannot pass]
-
A.
hasWrittenDialogueFor
Indicates that one entity has created or authored dialogue content for another entity, such as a work, project, or production.
-
B.
spokenInPartOf
Indicates that a language or dialect is spoken within a specific subregion or part of a larger geographic or administrative area.
-
C.
spokenToCharacter
chosen
Indicates that one character has verbally addressed or communicated directly with another character.
-
D.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
E.
speaksInFilm
Indicates that a person or character provides spoken dialogue or voice work within a particular film.
- 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_69f34901106881908ea893ad504a08be |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b643d5008190b789f0a4d3288fa3 |
completed | May 3, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:26 a.m.