Triple
T15357610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Octan Corporation |
E367202
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Bricksburg |
E367182
|
NE 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: Bricksburg | Statement: [Octan Corporation, operatesIn, Bricksburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bricksburg Context triple: [Octan Corporation, operatesIn, Bricksburg]
-
A.
Bricksburg
chosen
Bricksburg is the primary LEGO city setting in "The LEGO Movie," depicted as a bustling, highly structured world built entirely from LEGO bricks.
-
B.
Snowville
Snowville is a small rural settlement located within the township of Tehkummah in Ontario, Canada.
-
C.
Rivertown
Rivertown is a historic-themed district in Kenner, Louisiana, featuring museums, cultural attractions, and riverfront entertainment.
-
D.
Snickersville
Snickersville was the historic name of the rural village now known as Bluemont in Loudoun County, Virginia.
-
E.
Coolville
Coolville is a small village in southeastern Ohio, United States, known for its rural setting near the Hocking and Ohio rivers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2d4934819097fc63603964217c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b45e3048190a7fa62ead6916fed |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:18 a.m.