Triple
T20121757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GoldenEye satellite weapon |
E490624
|
entity |
| Predicate | numberOfUnitsInFiction |
P138770
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [GoldenEye satellite weapon, numberOfUnitsInFiction, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUnitsInFiction Context triple: [GoldenEye satellite weapon, numberOfUnitsInFiction, 2]
-
A.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
C.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
D.
eraWithinFiction
Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
-
E.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6673f5b4c8190bf9fb5f4e6b6a452 |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc2bc3c819088c33cd263303433 |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:30 p.m.