Triple
T297902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Beach |
E6132
|
entity |
| Predicate | cityDistrictNumber |
P8975
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [North Beach, cityDistrictNumber, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityDistrictNumber Context triple: [North Beach, cityDistrictNumber, 3]
-
A.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
B.
boroughNumber
chosen
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
-
C.
district
Indicates that one entity is an administrative or electoral district that geographically contains or governs another entity.
-
D.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
E.
militaryDistrict
Indicates that an entity functions as, or is located within, an administrative military district or region under military jurisdiction.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea4778cc8190be7b648a82542891 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e937af888190a0960708f09ae033 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.