Triple
T33566903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American Datum of 1927 |
E859783
|
entity |
| Predicate | hasManyLocalAdjustments |
P203101
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [North American Datum of 1927, hasManyLocalAdjustments, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManyLocalAdjustments Context triple: [North American Datum of 1927, hasManyLocalAdjustments, true]
-
A.
hasLocalCustom
Indicates that a particular place, group, or context possesses a distinctive local tradition, practice, or custom.
-
B.
isLocalOptionTax
Indicates that a tax is imposed at a local (e.g., city or county) level as an optional levy rather than as a mandatory statewide or national tax.
-
C.
hasMultipleLocalities
Indicates that an entity is associated with more than one locality or geographic area.
-
D.
isLocalQuantity
Indicates that a quantity is specific to a particular context, location, or subsystem rather than being globally applicable.
-
E.
hasLocalHistoricCommission
Indicates that an entity is subject to, overseen by, or associated with a local historic commission or preservation authority.
- 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01203ac018819085d7c9abd8345b23 |
completed | May 11, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_6a011f3f149c819090749722da0e3413 |
completed | May 11, 2026, 12:13 a.m. |
| PDg | Predicate description generation | batch_6a01203a1c188190874d87d148dfa8e4 |
completed | May 11, 2026, 12:18 a.m. |
Created at: May 1, 2026, 1:40 a.m.