Triple
T47362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of the United States |
E929
|
entity |
| Predicate | isStatus |
P127
|
FINISHED |
| Object | unpaid position |
—
|
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: unpaid position | Statement: [First Lady of the United States, isStatus, unpaid position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStatus Context triple: [First Lady of the United States, isStatus, unpaid position]
-
A.
status
chosen
Indicates the current condition, state, or standing of an entity within a given context.
-
B.
isOn
Indicates that one entity is physically positioned above and in contact with the top surface of another entity.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
hasIconicStatus
Indicates that an entity holds a widely recognized, emblematic, or culturally significant status within a particular domain or context.
-
E.
hasAuthorityStatus
Indicates that one entity holds a particular level or type of official power, control, or decision-making authority over another entity or within a defined context.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b1bf2c081908f20e13939b713ff |
completed | Feb. 28, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69a24abd07508190a83ffba5368c1c79 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.