Triple
T17846655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kfar Saba |
E445678
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Ofakim |
—
|
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: Ofakim | Statement: [Kfar Saba, hasSisterCity, Ofakim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ofakim Context triple: [Kfar Saba, hasSisterCity, Ofakim]
-
A.
Ofakim
chosen
Ofakim is a small development town in southern Israel known for its working-class character and location in the Negev region.
-
B.
Fakui
Fakui is the given name of Zhang Fakui, a notable Chinese military figure.
-
C.
Oimachi
Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the city.
-
D.
Ohoka
Ohoka is a small rural township in New Zealand’s Canterbury region, known for its lifestyle properties and proximity to Christchurch.
-
E.
Ogikubo
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffb35248190a80a428686e06d87 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.