Triple
T12932721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phrygian language |
E309422
|
entity |
| Predicate | laterScriptInfluence |
P77309
|
FINISHED |
| Object | Greek script |
—
|
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: Greek script | Statement: [Phrygian language, laterScriptInfluence, Greek script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterScriptInfluence Context triple: [Phrygian language, laterScriptInfluence, Greek script]
-
A.
scriptInfluence
chosen
Indicates that one script affects, shapes, or alters the behavior, outcome, or characteristics of another entity (such as another script, process, or system).
-
B.
hasSubsequentInfluence
Indicates that one entity has an influence or effect that occurs after, and is causally or temporally downstream from, another entity or event.
-
C.
influencesPlotOf
Indicates that one entity has an effect on or helps shape the storyline or narrative development of another entity.
-
D.
laterIn
Indicates that one event, state, or time point occurs after another in temporal order.
-
E.
spinOffInfluence
Indicates that one entity has influenced the creation, direction, or characteristics of another entity that is derived from it as a spin-off.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.