Triple
T23452941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weinheim |
E567834
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | HD |
—
|
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: HD | Statement: [Weinheim, hasVehicleRegistrationCode, HD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HD Context triple: [Weinheim, hasVehicleRegistrationCode, HD]
-
A.
HD
chosen
HD is the vehicle registration code used for the German city of Heidelberg.
-
B.
HD
HD is the standard astronomical abbreviation for the Henry Draper Catalogue, a widely used star catalog that assigns spectral classifications and identifiers to hundreds of thousands of stars.
-
C.
HD
HD is an inherited neurodegenerative disorder characterized by progressive motor dysfunction, cognitive decline, and psychiatric symptoms caused by a CAG repeat expansion in the huntingtin gene.
-
D.
HD
HD is a postcode area in the United Kingdom covering Huddersfield and its surrounding districts in West Yorkshire.
-
E.
HD
HD is the station code for Harda railway station, a rail transport facility serving the town of Harda in Madhya Pradesh, India.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a694f19081909117bc9b10ca8a83 |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:52 p.m.