Triple
T7326959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttlesford |
E168899
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Takeley |
E636436
|
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: Takeley | Statement: [Uttlesford, containsSettlement, Takeley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takeley Context triple: [Uttlesford, containsSettlement, Takeley]
-
A.
Takeley
chosen
Takeley is a village and civil parish in Essex, England, situated near London Stansted Airport.
-
B.
Takaro
Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
-
C.
Oyamazaki
Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
-
D.
Kitadake
Kitadake is one of the principal peaks of the active Sakurajima volcanic complex in Kagoshima Prefecture, Japan.
-
E.
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.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a755e88190a50126e2d1d6d4cb |
completed | March 27, 2026, 9:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef11f76881909d802942c4013509 |
completed | March 28, 2026, 3:09 p.m. |
Created at: March 27, 2026, 3:03 p.m.