Triple
T37829243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Broadsword |
E943150
|
entity |
| Predicate | BrazilianName |
P62257
|
FINISHED |
| Object | BNS Greenhalgh |
—
|
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: BNS Greenhalgh | Statement: [HMS Broadsword, BrazilianName, BNS Greenhalgh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BrazilianName Context triple: [HMS Broadsword, BrazilianName, BNS Greenhalgh]
-
A.
nameInBrazil
chosen
Indicates that an entity is known or referred to by a particular name specifically in the context of Brazil.
-
B.
nameInPortuguese
Indicates that an entity is referred to by a specific name when expressed in the Portuguese language.
-
C.
usedAsCharacterNameInBrazil
Indicates that a name is specifically used as a character name in Brazilian media or cultural contexts.
-
D.
nicknameInPortuguese
Indicates that one entity is used as a nickname for another entity specifically in the Portuguese language.
-
E.
countryNamePortuguese
Indicates the Portuguese-language name assigned to a given country.
- F. None of above.
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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.