Triple
T34969334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annorax |
E1008489
|
entity |
| Predicate | timelineEffect |
P182150
|
FINISHED |
| Object | creates alternate histories in the Delta Quadrant |
—
|
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: creates alternate histories in the Delta Quadrant | Statement: [Annorax, timelineEffect, creates alternate histories in the Delta Quadrant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timelineEffect Context triple: [Annorax, timelineEffect, creates alternate histories in the Delta Quadrant]
-
A.
showsEffect
Indicates that one entity produces, demonstrates, or reveals a particular effect or outcome on another entity or context.
-
B.
temporalEffect
Indicates a relationship where one event, state, or action produces consequences or changes that occur at a later time.
-
C.
timelineUse
Indicates that one entity utilizes or incorporates another entity within a temporal sequence or schedule (a timeline).
-
D.
arrowEffect
Indicates that one entity causes or produces a directional influence or outcome on another, similar to an arrow showing the effect from source to target.
-
E.
chronologicalEffect
Indicates that one event or state occurs as a temporal consequence of, or in sequence after, another.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.