Triple
T954426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. No |
E20594
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | M |
E109337
|
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: M | Statement: [Dr. No, featuresCharacter, M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M Context triple: [Dr. No, featuresCharacter, M]
-
A.
M
M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
-
B.
M
chosen
M is the codename for James Bond’s stern and authoritative superior who heads the British Secret Service in the 007 franchise.
-
C.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
D.
MR
MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
-
E.
MAR
MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3da8d508190b56b29d7f235d2c4 |
completed | March 1, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac119fd16c81908c43b6d3dc6d53b6 |
completed | March 7, 2026, 11:53 a.m. |
Created at: March 1, 2026, 7:40 p.m.