Triple
T4510098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Church |
E102029
|
entity |
| Predicate | hasNotableTitle |
P13335
|
FINISHED |
| Object | world’s first female flight attendant |
—
|
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: world’s first female flight attendant | Statement: [Ellen Church, hasNotableTitle, world’s first female flight attendant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTitle Context triple: [Ellen Church, hasNotableTitle, world’s first female flight attendant]
-
A.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
B.
hadTitle
chosen
Indicates that an entity held or was assigned a specific title or formal designation.
-
C.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
D.
hasNotablePhrase
Indicates that an entity is associated with a specific phrase or expression that is considered notable or characteristic of it.
-
E.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5712b9308190876c117b50d12635 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd5218afb4819087c99e0a1f22e137 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.