Triple
T12117413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keningau |
E288600
|
entity |
| Predicate | roadConnectedTo |
P11435
|
FINISHED |
| Object | Tenom |
E288601
|
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: Tenom | Statement: [Keningau, roadConnectedTo, Tenom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tenom Context triple: [Keningau, roadConnectedTo, Tenom]
-
A.
Tenom
chosen
Tenom is a rural interior town and district in the Malaysian state of Sabah, known for its agriculture, coffee production, and Murut cultural heritage.
-
B.
Totma
Totma is a historic town in northwestern Russia known for its distinctive baroque churches and role as a former trading center in the Vologda region.
-
C.
Teno
Teno is a Chilean municipality and town located in the Curicó Province of the Maule Region, known for its agricultural activities and rural character.
-
D.
Tenjo
Tenjo is a small municipality and town in the department of Cundinamarca, Colombia, known for its rural landscapes and proximity to Bogotá.
-
E.
Tenjo
Tenjo is a district in West Java, Indonesia, known as part of the greater Bogor area on the outskirts of Jakarta.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915760d208190b68f5e024b3676ba |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a75f77881908345a585a689f69f |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:49 p.m.