Triple
T32989667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orangewomen |
E844048
|
entity |
| Predicate | nicknameStatus |
P101915
|
FINISHED |
| Object | retired |
—
|
LITERAL 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: retired | Statement: [Orangewomen, nicknameStatus, retired]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameStatus Context triple: [Orangewomen, nicknameStatus, retired]
-
A.
hasNicknameStatus
chosen
Indicates that an entity holds a particular status or classification specifically related to its nickname.
-
B.
nameStatus
Indicates the status or condition associated with an entity’s name, such as whether it is current, preferred, alternate, or deprecated.
-
C.
namesakeStatus
Indicates that one entity serves as the namesake of another, or that two entities share a relationship based on having the same name.
-
D.
nicknameCategory
Indicates that one entity is a nickname and the other entity is the category or type that this nickname belongs to.
-
E.
isNickname
Indicates that one name is an informal or alternative name commonly used to refer to the same person or entity as another name.
- 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_69f3494d99988190b502c68926af2c4d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d212e0b08190891229dff46e7ca7 |
completed | May 3, 2026, 4:41 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe5f93c8190995c53dbbe380a32 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:22 a.m.