Triple
T31439532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogueport Inn |
E802028
|
entity |
| Predicate | belongsToTownArea |
P85719
|
FINISHED |
| Object | Rogueport main plaza vicinity |
—
|
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: Rogueport main plaza vicinity | Statement: [Rogueport Inn, belongsToTownArea, Rogueport main plaza vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToTownArea Context triple: [Rogueport Inn, belongsToTownArea, Rogueport main plaza vicinity]
-
A.
hasAreaName
Indicates that an entity is associated with a specific named geographic or administrative area.
-
B.
hasMunicipalArea
Indicates that an entity (typically an administrative unit or municipality) possesses or is associated with a specific municipal area.
-
C.
regionOfTown
Indicates that one entity is a specific area or district that forms part of a town.
-
D.
belongsToUrbanZone
chosen
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
E.
containsSuburbanAreaOf
Indicates that one geographic region includes within its boundaries a suburban area belonging to or associated with another region.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe7b1c506c8190869c1a22031e0571 |
completed | May 9, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69fe796b2bdc8190a86980d44008f875 |
completed | May 9, 2026, 12:01 a.m. |
Created at: April 30, 2026, 9:04 p.m.