Triple
T38484345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Colchester government |
E917872
|
entity |
| Predicate | hasAppointedOffice |
P179917
|
FINISHED |
| Object | Town Manager of Colchester |
—
|
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: Town Manager of Colchester | Statement: [Town of Colchester government, hasAppointedOffice, Town Manager of Colchester]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAppointedOffice Context triple: [Town of Colchester government, hasAppointedOffice, Town Manager of Colchester]
-
A.
hasAppointedOfficial
chosen
Indicates that one entity has formally selected and installed another entity into an official position or role.
-
B.
isAppointed
Indicates that an authority formally assigns a person to a specific role, position, or responsibility.
-
C.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
D.
usesElectedOffice
Indicates that an entity makes use of or leverages an elected public office in relation to another entity or context.
-
E.
wasAppointed
Indicates that an entity has been officially assigned or designated to a position, role, or office by an authority or decision-making body.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:31 p.m.