Triple
T12091769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakinada district |
E287958
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Samarlakota |
E787180
|
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: Samarlakota | Statement: [Kakinada district, hasTown, Samarlakota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samarlakota Context triple: [Kakinada district, hasTown, Samarlakota]
-
A.
Samarlakota
chosen
Samarlakota is a town in the Indian state of Andhra Pradesh known for its historic temples and regional cultural significance.
-
B.
Lanao
Lanao was a former province in the Philippines on the island of Mindanao that was later divided into Lanao del Norte and Lanao del Sur.
-
C.
Lanao
Lanao is a coastal barangay in the municipality of Daanbantayan in Cebu, Philippines.
-
D.
Sarangani
Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
-
E.
Batan
Batan is a coastal municipality in the province of Aklan in the Philippines, known for its agricultural economy and proximity to Capiz.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9151797988190b0d007ea806bcf02 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66d1b44819091f638d2a621ecde |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.