Triple
T31450687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qené poetry |
E802311
|
entity |
| Predicate | hasInterpretiveLevels |
P199558
|
FINISHED |
| Object | surface meaning |
—
|
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: surface meaning | Statement: [Qené poetry, hasInterpretiveLevels, surface meaning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterpretiveLevels Context triple: [Qené poetry, hasInterpretiveLevels, surface meaning]
-
A.
hasInterpretiveElement
Indicates that something includes or is associated with an element involving interpretation, such as a subjective, analytical, or explanatory component.
-
B.
hasInterpretiveSigns
Indicates that interpretive or informational signs are present at or associated with the subject.
-
C.
hasInterpretiveService
Indicates that an entity provides or is associated with interpretive services (such as translation, sign language, or explanatory guidance) for another entity or context.
-
D.
hasInterpretationStyle
Indicates a relationship where an entity is associated with a particular manner, method, or style in which it is interpreted or understood.
-
E.
hasInterpretiveGoal
Indicates that an entity is associated with a specific intended meaning, purpose, or objective guiding how something should be interpreted.
- F. None of above. chosen
Provenance (4 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
| PDg | Predicate description generation | batch_69ff45782cb88190b604811e4d724382 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 30, 2026, 9:12 p.m.