Triple
T38698211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France (fictional) |
E950061
|
entity |
| Predicate | hasTemporalVariant |
P198454
|
FINISHED |
| Object | future France (fictional) |
—
|
NE NERFINISHED |
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: future France (fictional) | Statement: [France (fictional), hasTemporalVariant, future France (fictional)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalVariant Context triple: [France (fictional), hasTemporalVariant, future France (fictional)]
-
A.
hasTemporalVariabilityIn
Indicates that something exhibits variation or change over time within a specified temporal context or interval.
-
B.
hasTemporalUse
Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
-
C.
hasTemporalAttribute
Indicates that an entity is associated with a specific temporal property or characteristic, such as time, duration, or period.
-
D.
hadTemporalities
Indicates that something possessed or was associated with specific temporal characteristics, durations, or time-related states.
-
E.
hasTemporalDefinition
Indicates that something is associated with a definition or specification that is constrained or characterized by time.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
| PDg | Predicate description generation | batch_69fee33485188190a43526c9d39e3b6a |
completed | May 9, 2026, 7:33 a.m. |
Created at: May 3, 2026, 4:33 p.m.