Triple
T1640885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reginald Warneford |
E35467
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Darjeeling |
E162673
|
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: Darjeeling | Statement: [Reginald Warneford, placeOfBirth, Darjeeling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darjeeling Context triple: [Reginald Warneford, placeOfBirth, Darjeeling]
-
A.
Darjeeling
chosen
Darjeeling is a famous hill station in the Indian Himalayas renowned for its tea plantations, scenic mountain views, and colonial-era charm.
-
B.
Jalpaiguri
Jalpaiguri is a town in northeastern India known as an important administrative and commercial center near the Himalayan foothills.
-
C.
Nainital
Nainital is a popular hill station and lake town in northern India, known for its scenic beauty and colonial-era charm.
-
D.
Mussoorie
Mussoorie is a popular hill station in the Indian state of Uttarakhand, known for its scenic Himalayan views, colonial-era architecture, and role as a major educational and administrative training hub.
-
E.
Ooty
Ooty is a popular hill station in the Nilgiri Hills of southern India, known for its cool climate, tea plantations, and scenic mountain landscapes.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a3c883c8190bec1d87ecedf2575 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad609cf8488190ba334bdff2c5e78d |
completed | March 8, 2026, 11:42 a.m. |
Created at: March 4, 2026, 7:28 p.m.