Triple
T387430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sekai Holland |
E8808
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sekai Holland |
E8808
|
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: Sekai Holland | Statement: [Sekai Holland, name, Sekai Holland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sekai Holland Context triple: [Sekai Holland, name, Sekai Holland]
-
A.
Sekai Holland
chosen
Sekai Holland is a Zimbabwean politician, human rights activist, and co-founder of the Movement for Democratic Change known for her long struggle for democracy and social justice.
-
B.
Harborland
Harborland is a popular waterfront shopping and entertainment district in Kobe, Japan, known for its modern malls, restaurants, and scenic harbor views.
-
C.
Kalorama
Kalorama is an affluent, historic residential neighborhood in Northwest Washington, D.C., known for its embassies, stately mansions, and prominent political residents.
-
D.
Kamen
Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
-
E.
Sendagaya
Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5828d881909e8810061c02480c |
completed | Feb. 28, 2026, 1:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a405f576148190b058300c3bd0d032 |
completed | March 1, 2026, 9:25 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.