Triple
T19597953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi High Court |
E470396
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | DHC |
—
|
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: DHC | Statement: [Delhi High Court, abbreviation, DHC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DHC Context triple: [Delhi High Court, abbreviation, DHC]
-
A.
DHC
chosen
DHC is the commonly used abbreviation for the Delhi High Court, one of the principal high courts in India with jurisdiction over the National Capital Territory of Delhi.
-
B.
Kiehl's
Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
-
C.
Shiseido
Shiseido is a major Japanese multinational cosmetics and skincare company known for its high-end beauty products and long-standing global presence.
-
D.
Garnier
Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
-
E.
Nivea
Nivea is an American R&B singer best known for her early-2000s hits like "Don't Mess with My Man" and collaborations with prominent hip-hop artists.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407c52c081908704d3a4dd6e853b |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.