Triple
T2513136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago |
E52745
|
entity |
| Predicate | languageCharacterSpeaks |
P34466
|
FINISHED |
| Object | Spanish (in-story, rendered in English) |
—
|
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: Spanish (in-story, rendered in English) | Statement: [Santiago, languageCharacterSpeaks, Spanish (in-story, rendered in English)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCharacterSpeaks Context triple: [Santiago, languageCharacterSpeaks, Spanish (in-story, rendered in English)]
-
A.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
B.
spokenAlong
Indicates that two or more languages are used concurrently or within the same context in a particular place, time, or situation.
-
C.
speaksIn
chosen
Indicates that an entity uses or expresses itself in a particular language or medium when speaking.
-
D.
soundCharacter
Indicates a relationship where one entity specifies the quality, style, or distinguishing characteristics of a sound produced or perceived in another entity.
-
E.
aiCharacter
Indicates that an entity is a character or agent whose behavior or role is driven by artificial intelligence.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.