Triple
T271928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACM Professional Chapters |
E5651
|
entity |
| Predicate | hasGeographicCoverage |
P2178
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [ACM Professional Chapters, hasGeographicCoverage, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicCoverage Context triple: [ACM Professional Chapters, hasGeographicCoverage, global]
-
A.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
B.
geographicContext
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
-
C.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
D.
geographicDistribution
chosen
Indicates the spatial range or area over which something occurs, exists, or is found.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.