Triple
T16964416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vattezhuthu |
E411506
|
entity |
| Predicate | influencedScript |
P77309
|
FINISHED |
| Object | modern Malayalam 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: modern Malayalam script | Statement: [Vattezhuthu, influencedScript, modern Malayalam script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedScript Context triple: [Vattezhuthu, influencedScript, modern Malayalam 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.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
influencesPlotOf
Indicates that one entity has an effect on or helps shape the storyline or narrative development of another entity.
-
D.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
E.
influencedByCurrent
Indicates that something’s state, behavior, or outcome is affected or determined by the current conditions, context, or situation.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a2cda88190bd574a869f0e43e9 |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e32b9cddf88190bc42709604047353 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.