Triple
T700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everett, Massachusetts |
E13
|
entity |
| Predicate | demographicsNote |
P232
|
FINISHED |
| Object | historically working-class community |
—
|
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: historically working-class community | Statement: [Everett, Massachusetts, demographicsNote, historically working-class community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicsNote Context triple: [Everett, Massachusetts, demographicsNote, historically working-class community]
-
A.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
dateOfBirth
Indicates the specific calendar date on which an individual or entity was born.
-
C.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
D.
placeOfBirth
Indicates the location where a person or other entity was born.
-
E.
notableRecipient
Indicates that an entity has received a notable award, honor, or recognition from 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a23211181c81909c2db8796d2aded4 |
completed | Feb. 28, 2026, 12:08 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.