Triple
T32972704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte (About Time) |
E843567
|
entity |
| Predicate | temporalSettingOfAppearance |
P97182
|
FINISHED |
| Object | early part of the film’s timeline |
—
|
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: early part of the film’s timeline | Statement: [Charlotte (About Time), temporalSettingOfAppearance, early part of the film’s timeline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalSettingOfAppearance Context triple: [Charlotte (About Time), temporalSettingOfAppearance, early part of the film’s timeline]
-
A.
timeOfAppearance
Indicates the specific time at which an entity or event becomes visible, present, or first occurs.
-
B.
hasTemporalLocation
Indicates that something occurs, exists, or is valid during a specific time or time interval.
-
C.
appearsInTimePeriodDepicted
Indicates that something is present or occurs within the specific time period that is depicted or represented.
-
D.
appearsInTimePeriod
chosen
Indicates that an entity is present, active, or occurs within a specified time period.
-
E.
settingOfFirstAppearance
Indicates the location or context in which an entity is first introduced or appears.
- F. None of above.
Provenance (3 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_69f3494b9fc48190bb61c955ba471275 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:22 a.m.