Triple
T6266688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | May-Britt |
E140429
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Britt |
E252850
|
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: Britt | Statement: [May-Britt, hasComponent, Britt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Britt Context triple: [May-Britt, hasComponent, Britt]
-
A.
Britt
chosen
Britt is the laconic, knife-throwing gunfighter portrayed by James Coburn in the classic Western film "The Magnificent Seven."
-
B.
Tessa
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
-
C.
Brenna
Brenna is a Norwegian surname most notably borne by Tonje Brenna, a contemporary Norwegian politician.
-
D.
Greta
Greta is a small town located within the Hunter Region of New South Wales, Australia.
-
E.
Greta
Greta is a feminine given name, commonly used as a diminutive or variant of names like Margaret in various European languages.
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0639fdad081908492c44d369df8c5 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c51939cc6081909e491bd16fab595b |
completed | March 26, 2026, 11:32 a.m. |
Created at: March 22, 2026, 4:25 p.m.