Triple
T16932301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Drexel |
E410739
|
entity |
| Predicate | hasToneAroundEvents |
P124796
|
FINISHED |
| Object | darkly comic |
—
|
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: darkly comic | Statement: [Norman Drexel, hasToneAroundEvents, darkly comic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToneAroundEvents Context triple: [Norman Drexel, hasToneAroundEvents, darkly comic]
-
A.
hasNearbyEvent
Indicates that an event occurs close in space or time to the referenced entity.
-
B.
hasNearbyEventType
Indicates that an event of a specified type occurs in close spatial or contextual proximity to a given reference entity or location.
-
C.
hasSideEvent
Indicates that an event is associated with an additional, related side event occurring alongside it.
-
D.
hasCompanionEvent
Indicates that one event is associated with another event that occurs alongside it as a related or accompanying occurrence.
-
E.
hasGroundEventsAlong
Indicates that certain ground-based events occur or are present along a specified path, route, or linear feature.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2650e08190b669d0cf2cf1275b |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32d7aae948190bc238d765795688c |
completed | April 18, 2026, 7:06 a.m. |
Created at: April 10, 2026, 5:30 a.m.