Triple
T26137547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malekshahi |
E659422
|
entity |
| Predicate | tenseAspectSystem |
P5214
|
FINISHED |
| Object | past vs non-past opposition |
—
|
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: past vs non-past opposition | Statement: [Malekshahi, tenseAspectSystem, past vs non-past opposition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tenseAspectSystem Context triple: [Malekshahi, tenseAspectSystem, past vs non-past opposition]
-
A.
hasTenseAspectSystem
chosen
Indicates that a language or clause employs a particular system for expressing tense and aspect distinctions.
-
B.
hasTenseAspect
Indicates that a verb or clause is associated with a specific grammatical tense and aspect configuration.
-
C.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
D.
hasTense
Indicates that an action, event, or state is associated with a specific grammatical tense (such as past, present, or future).
-
E.
hasVerbAspect
Indicates that a verb or verbal expression is associated with a particular grammatical aspect (such as perfective, imperfective, or progressive) describing the temporal structure of the action or state.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60be1d2408190820365bf7d8436bd |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:18 p.m.