Triple
T23238239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zulia |
E581362
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Lara State |
—
|
NE NERFINISHED |
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: Lara State | Statement: [Zulia, borders, Lara State]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lara State Context triple: [Zulia, borders, Lara State]
-
A.
Lara State
chosen
Lara State is a federal state in northwestern Venezuela known for its capital Barquisimeto, a major cultural and economic center.
-
B.
Tharoch State
Tharoch State was a small princely hill state in the Simla Hills region of colonial India, ruled by local chiefs under British suzerainty.
-
C.
Jaora State
Jaora State was a princely state in British India, located in what is now Madhya Pradesh and ruled by a Muslim dynasty under British suzerainty.
-
D.
Las Bela State
Las Bela State was a former princely state in the Baluchistan region of British India, located along the Arabian Sea coast in what is now southwestern Pakistan.
-
E.
Kalsia State
Kalsia State was a small princely state in colonial India located in the Cis-Sutlej region of present-day Punjab and Haryana.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192ea590c81908cd677d89f67d49f |
completed | April 29, 2026, 5:11 a.m. |
Created at: April 17, 2026, 4:09 p.m.