Triple
T24731202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taznatit |
E618291
|
entity |
| Predicate | influencedAspectOf |
P157823
|
FINISHED |
| Object | Korandje lexicon |
—
|
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: Korandje lexicon | Statement: [Taznatit, influencedAspectOf, Korandje lexicon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedAspectOf Context triple: [Taznatit, influencedAspectOf, Korandje lexicon]
-
A.
influencedAspectOf
chosen
Indicates that one entity has affected, shaped, or altered a particular aspect or component of another entity.
-
B.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
C.
influencesThrough
Indicates that one entity affects or alters another entity indirectly by means of an intermediate factor, channel, or mechanism.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 4:02 a.m.