Triple
T17907429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigel Uno |
E447736
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Sector V |
—
|
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: Sector V | Statement: [Nigel Uno, memberOf, Sector V]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sector V Context triple: [Nigel Uno, memberOf, Sector V]
-
A.
Sector V
chosen
Sector V is the primary group of child operatives featured in the animated series "Codename: Kids Next Door," known for battling adult tyranny with imaginative gadgets and missions.
-
B.
Sector V
Sector V is a major information technology and business district in Bidhannagar (Salt Lake City), Kolkata, known for its concentration of IT parks, corporate offices, and tech companies.
-
C.
Sector 7
Sector 7 is a residential and commercial neighborhood within the North Karachi area of Karachi, Pakistan.
-
D.
Sector 6
Sector 6 is one of the administrative sectors of Bucharest, Romania, encompassing several western neighborhoods of the city.
-
E.
Sector 5
Sector 5 is a residential and commercial neighborhood within the North Karachi area of Karachi, Pakistan.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9d458881909e35e1c7a6e85436 |
completed | April 19, 2026, 9:21 a.m. |
Created at: April 10, 2026, 10:19 a.m.