Triple
T11858231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ekeremor |
E282093
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Ekeremor Town |
E951698
|
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: Ekeremor Town | Statement: [Ekeremor, hasSettlement, Ekeremor Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ekeremor Town Context triple: [Ekeremor, hasSettlement, Ekeremor Town]
-
A.
Ekeremor Town
chosen
Ekeremor Town is a principal urban center and administrative hub in Bayelsa State, Nigeria.
-
B.
Poros town
Poros town is the main settlement and harbor of the Greek island of Poros in the Saronic Gulf, known for its neoclassical waterfront, vibrant marina, and role as a popular weekend getaway from Athens.
-
C.
Lyari Town
Lyari Town is one of Karachi’s oldest and most densely populated neighborhoods, known for its vibrant working-class culture, political activism, and history of gang-related violence.
-
D.
Yoron Town
Yoron Town is a small island municipality in Kagoshima Prefecture, Japan, known for its subtropical climate, coral reefs, and white-sand beaches.
-
E.
Ekeremor
Ekeremor is a local government area in Nigeria’s oil-rich Niger Delta region, known for its riverine communities and location within Bayelsa State.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a699089c8190b7a298baf13dcded |
completed | April 10, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f417a954e881909fdd9626d41229e2 |
completed | May 1, 2026, 3:02 a.m. |
Created at: April 8, 2026, 9:43 p.m.