Triple
T35177318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abigail Sherman |
E1015743
|
entity |
| Predicate | spouseRegion |
P196674
|
FINISHED |
| Object | New England |
—
|
NE NERFINISHED |
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: New England | Statement: [Abigail Sherman, spouseRegion, New England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseRegion Context triple: [Abigail Sherman, spouseRegion, New England]
-
A.
spouseState
Indicates the marital status or condition of a person’s spouse in relation to them.
-
B.
spouse2Nationality
Indicates that the second spouse in a marital relationship has a specified nationality.
-
C.
spouseCountryOfCitizenship
Indicates the country in which a person's spouse holds legal citizenship.
-
D.
spouseIn
Indicates that one entity is the spouse (married partner) of another entity within a specified context or grouping.
-
E.
spouseOfOfficeHolderJurisdiction
Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
- F. None of above. chosen
Provenance (4 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69fe610d75a48190bfd08a9bb957fcd3 |
completed | May 8, 2026, 10:17 p.m. |
Created at: May 3, 2026, 4:02 p.m.