Triple
T28516569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Quinn Christensen |
E721633
|
entity |
| Predicate | placeOfResidenceDuringSpouseCareer |
P127244
|
FINISHED |
| Object | Massachusetts |
—
|
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: Massachusetts | Statement: [Christine Quinn Christensen, placeOfResidenceDuringSpouseCareer, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeOfResidenceDuringSpouseCareer Context triple: [Christine Quinn Christensen, placeOfResidenceDuringSpouseCareer, Massachusetts]
-
A.
residenceDuringCareer
Indicates the place where an individual lived for a significant period while pursuing their professional career.
-
B.
residenceDuringLaterYearsOfSpouse
Indicates that an entity lived in a particular place during the later years of their spouse’s life.
-
C.
residenceDuringSpouseGovernorship
chosen
Indicates that a person resided in a particular place during the period when their spouse was serving as governor.
-
D.
residenceDuringMarriage
Indicates the place where spouses lived or maintained their home during the period of their marriage.
-
E.
residenceAfterCareer
Indicates the place where an individual lives or settles after the conclusion of their professional career.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 28, 2026, 3:17 a.m.