Triple
T20067065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persian honorifics |
E499634
|
entity |
| Predicate | convey |
P59910
|
FINISHED |
| Object | respect |
—
|
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: respect | Statement: [Persian honorifics, convey, respect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convey Context triple: [Persian honorifics, convey, respect]
-
A.
conjugate
Indicates that one entity is a grammatical or mathematical counterpart of another, linked by a specific transformation such as verb inflection or complex-number pairing.
-
B.
conveysAttribute
chosen
Indicates that one entity communicates, expresses, or imparts a particular attribute or quality to another entity.
-
C.
to
Indicates a directional or goal-oriented relationship in which something is directed, transferred, or oriented toward a target or endpoint.
-
D.
prevede
Indicates that an entity plans, foresees, or provides in advance for another entity, event, or outcome.
-
E.
conveysStyle
Indicates that one entity expresses, communicates, or embodies a particular style through its form, behavior, or presentation.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66379f2cc81908f13a7b216878f12 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:39 p.m.