Triple
T2564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambridge, Massachusetts |
E48
|
entity |
| Predicate | mayorType |
P174
|
FINISHED |
| Object | ceremonial mayor |
—
|
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: ceremonial mayor | Statement: [Cambridge, Massachusetts, mayorType, ceremonial mayor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayorType Context triple: [Cambridge, Massachusetts, mayorType, ceremonial mayor]
-
A.
officialName
Indicates the formally recognized name assigned to an entity by an authoritative body or source.
-
B.
administeredBy
Indicates that an action, service, or process is carried out, managed, or overseen by a specified agent or authority.
-
C.
elects
Indicates that one entity selects or chooses another entity for a position, role, or office, typically through a formal voting process.
-
D.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
E.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
- 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_69a22e0d37588190897cf37a323013f5 |
completed | Feb. 27, 2026, 11:51 p.m. |
| NER | Named-entity recognition | batch_69a2316d88a08190b2e03041674b5674 |
completed | Feb. 28, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69a230c3ee4481908216244c38aa8aef |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a2316cbe58819096cc036d6e3b103c |
completed | Feb. 28, 2026, 12:06 a.m. |
Created at: Feb. 27, 2026, 11:55 p.m.