Triple
T1038662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Dowdeswell |
E22420
|
entity |
| Predicate | assumedOffice |
P7411
|
FINISHED |
| Object | 2014-09-23 |
—
|
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: 2014-09-23 | Statement: [Elizabeth Dowdeswell, assumedOffice, 2014-09-23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assumedOffice Context triple: [Elizabeth Dowdeswell, assumedOffice, 2014-09-23]
-
A.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
B.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
-
C.
electedOffice
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
D.
servesAsOfficeOf
Indicates that one entity functions as the official office, headquarters, or administrative base for another entity.
-
E.
positionInaugurated
chosen
Indicates that a person formally assumed a specific position or office at a particular point in time.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.