Triple
T1952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belmont, Massachusetts |
E36
|
entity |
| Predicate | hasReputationFor |
P22
|
FINISHED |
| Object | affluent residential character |
—
|
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: affluent residential character | Statement: [Belmont, Massachusetts, hasReputationFor, affluent residential character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReputationFor Context triple: [Belmont, Massachusetts, hasReputationFor, affluent residential character]
-
A.
notableFor
chosen
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
recognizedAs
Indicates that one entity is acknowledged or accepted as having the identity, role, status, or classification of another entity.
-
C.
hasNotableMember
Indicates that a group, organization, or collection includes at least one member who is distinguished or noteworthy in some significant way.
-
D.
grantedTo
Indicates that a right, permission, or resource has been formally given or assigned by one party to another.
-
E.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
- 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_69a22cde80848190b62c5f556b4d62ba |
completed | Feb. 27, 2026, 11:46 p.m. |
| NER | Named-entity recognition | batch_69a2346846608190b6b40d31f1dbd685 |
completed | Feb. 28, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69a233c396ec8190986608d07fb251d4 |
completed | Feb. 28, 2026, 12:16 a.m. |
Created at: Feb. 27, 2026, 11:48 p.m.