Triple
T12185131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deadline |
E290313
|
entity |
| Predicate | hasFictionalWar |
P103638
|
FINISHED |
| Object | interplanetary conflict |
—
|
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: interplanetary conflict | Statement: [Deadline, hasFictionalWar, interplanetary conflict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalWar Context triple: [Deadline, hasFictionalWar, interplanetary conflict]
-
A.
hasFictionalUniverseConflict
Indicates that there is a conflict or incompatibility between the fictional universes associated with the related entities.
-
B.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
C.
hasNotableWar
Indicates that an entity is associated with a significant or historically important war.
-
D.
hasFictionalIssue
Indicates that one entity possesses, is associated with, or is characterized by a particular fictional problem, flaw, or complication.
-
E.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d91a7e0fc081909ec9769231e728a4 |
completed | April 10, 2026, 3:42 p.m. |
Created at: April 8, 2026, 9:50 p.m.