Triple
T13419411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Callahan |
E313298
|
entity |
| Predicate | ageInMainTimeline |
P94404
|
FINISHED |
| Object | 19 |
—
|
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: 19 | Statement: [Nancy Callahan, ageInMainTimeline, 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageInMainTimeline Context triple: [Nancy Callahan, ageInMainTimeline, 19]
-
A.
ageDuringNarration
Indicates that an entity has a specified age at the time when the described narrative or event is taking place.
-
B.
timeRelativeToBirth
Indicates the temporal position of an event or state relative to an entity’s birth (e.g., before, at, or after birth).
-
C.
ageDuringMainEvents
chosen
Indicates the age an entity has at the time when the main events of a referenced context or narrative occur.
-
D.
ageInSeries
Indicates the age of an entity as it appears or is depicted within a specific series or installment of a work.
-
E.
inUniverseAge
Indicates the age of an entity as measured within the timeline or continuity of a specific fictional or defined universe.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb98e808190948013e8f24779c6 |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.