Triple
T17268459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sri Maharaja Kertajaya |
E419190
|
entity |
| Predicate | chronicleRole |
P101050
|
FINISHED |
| Object | antagonist to Ken Arok |
—
|
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: antagonist to Ken Arok | Statement: [Sri Maharaja Kertajaya, chronicleRole, antagonist to Ken Arok]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronicleRole Context triple: [Sri Maharaja Kertajaya, chronicleRole, antagonist to Ken Arok]
-
A.
chronicleScope
Indicates the temporal or contextual span over which an event, process, or narrative is recorded or documented.
-
B.
chronicledBy
Indicates that something is documented, recorded, or described in detail by a particular source, author, or record.
-
C.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
inNarrativeRole
chosen
Indicates that one entity participates in relation to another by occupying a specific narrative function or role within a story or discourse.
-
E.
metaNarrativeRole
Indicates the narrative function or role that one element (such as a character, voice, or device) plays in commenting on, framing, or reflecting the story itself at a meta-level.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4683c4819083a210255662136c |
completed | April 19, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:40 a.m.