Triple
T10618204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kharia |
E295177
|
entity |
| Predicate | hasTenseMarking |
P84925
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kharia, hasTenseMarking, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenseMarking Context triple: [Kharia, hasTenseMarking, true]
-
A.
hasTense
Indicates that an action, event, or state is associated with a specific grammatical tense (such as past, present, or future).
-
B.
hasTenseAspectMoodMarkers
chosen
Indicates that an expression includes explicit markers specifying its tense, aspect, and/or mood.
-
C.
hasTenseAspect
Indicates that a verb or clause is associated with a specific grammatical tense and aspect configuration.
-
D.
hasTenseAspectSystem
Indicates that a language or clause employs a particular system for expressing tense and aspect distinctions.
-
E.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d6df6ee1848190a7d5fcd40b06cfe3 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7a223c8190854409d76368f3e8 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 8:19 p.m.