Triple
T5723630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mintaka |
E126207
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Mintaka D |
E126207
|
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: Mintaka D | Statement: [Mintaka, hasComponent, Mintaka D]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mintaka D Context triple: [Mintaka, hasComponent, Mintaka D]
-
A.
Mintaka
chosen
Mintaka is a bright multiple star system in the constellation Orion, forming one of the three prominent stars of Orion’s Belt.
-
B.
Manda
Manda is a lesser-known Dravidian language spoken by tribal communities in parts of eastern India, particularly in Odisha.
-
C.
Nakanamanga
Nakanamanga is an Oceanic Austronesian language spoken primarily on Efate Island and nearby areas in Vanuatu.
-
D.
Mangina
Mangina is a town in North Kivu Province in the eastern Democratic Republic of the Congo that gained international attention as a focal point of the 2018–2020 Kivu Ebola epidemic.
-
E.
Mineta
Mineta is a Japanese surname most prominently associated with Norman Mineta, a longtime U.S. politician and former Secretary of Transportation.
- 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02506d8288190b33bede6c22af773 |
completed | March 22, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a15c74688190a40337000b4aa240 |
completed | March 23, 2026, 2:11 a.m. |
Created at: March 22, 2026, 3:47 p.m.