Triple
T7178760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Zakheim |
E167388
|
entity |
| Predicate | spouseOfEthnicOrigin |
P59312
|
FINISHED |
| Object | Polish-born American |
—
|
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: Polish-born American | Statement: [Helen Zakheim, spouseOfEthnicOrigin, Polish-born American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfEthnicOrigin Context triple: [Helen Zakheim, spouseOfEthnicOrigin, Polish-born American]
-
A.
spouseEthnicity
chosen
Indicates the ethnic background or identity of a person’s spouse.
-
B.
spouseOfHead
Indicates that one person is the married partner of the individual who holds the position of head (e.g., head of a household, organization, or state).
-
C.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
D.
spouseCountryOfCitizenship
Indicates the country in which a person's spouse holds legal citizenship.
-
E.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.