Triple
T8179713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consett |
E191026
|
entity |
| Predicate | postcodeArea |
P920
|
FINISHED |
| Object | DH |
E283608
|
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: DH | Statement: [Consett, postcodeArea, DH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DH Context triple: [Consett, postcodeArea, DH]
-
A.
DH
DH is the official abbreviation for Puerto Rico’s Department of Treasury, the government agency responsible for managing the island’s fiscal and tax affairs.
-
B.
DH
DH is the commonly used currency symbol representing the Moroccan dirham.
-
C.
DH
chosen
DH is the postcode area covering Durham and surrounding parts of North East England in the United Kingdom.
-
D.
DH
DH is the regional vehicle registration code assigned to motor vehicles registered in Kupang, Indonesia.
-
E.
DHM
DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4abd9768819091298e4dd995ac96 |
completed | March 31, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf86f8848190a196f7c8d3ad2b36 |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 5:40 p.m.