Triple
T32052479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States (internal district boundary only) |
E818525
|
entity |
| Predicate | mayOverlapIn |
P173155
|
FINISHED |
| Object | special-purpose districts |
—
|
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: special-purpose districts | Statement: [United States (internal district boundary only), mayOverlapIn, special-purpose districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayOverlapIn Context triple: [United States (internal district boundary only), mayOverlapIn, special-purpose districts]
-
A.
mayCross
Indicates that one entity is permitted or allowed to cross or pass over another entity or boundary.
-
B.
mayMeet
Indicates that one entity is permitted or has the possibility to meet or come together with another entity.
-
C.
mayExtendTo
Indicates that something has the potential or permission to reach, continue, or be applied up to a specified limit, scope, or boundary.
-
D.
overlapsWith
Indicates that two entities share a common part or region in space, time, or extent, but neither is completely contained within the other.
-
E.
mayMatch
Indicates a potential or permissible correspondence or pairing between two entities, without guaranteeing that the match actually occurs.
- 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_69f348fdacec8190b9f74375ca3b2094 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b4ca85188190b4f7ab81498a3d86 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b154b3dc819087115f5f63f7b00f |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b267b90c8190807208cadce5ae8d |
completed | May 3, 2026, 2:26 a.m. |
Created at: May 1, 2026, 12:20 a.m.