Triple
T33593121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvonne Carmichael |
E860482
|
entity |
| Predicate | lifeSituationAtStart |
P160191
|
FINISHED |
| Object | seemingly stable family life |
—
|
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: seemingly stable family life | Statement: [Yvonne Carmichael, lifeSituationAtStart, seemingly stable family life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lifeSituationAtStart Context triple: [Yvonne Carmichael, lifeSituationAtStart, seemingly stable family life]
-
A.
lifeSituation
Indicates the general circumstances, conditions, or context in which an entity’s life currently exists or unfolds.
-
B.
lifeStatusAtStart
chosen
Indicates the life status or condition of an entity at the beginning of a specified event or time period.
-
C.
lifeStatus
Indicates the current state of an entity’s existence, such as whether it is alive, dead, or in another defined life condition.
-
D.
situationType
Indicates the general kind or category of situation, event, or circumstance that a given instance represents.
-
E.
residenceAtStartOfFilm
Indicates the place where a person or character is living at the beginning of the film.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f79d60308190bf1a3ce07f1c5ed1 |
completed | May 3, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.