Triple
T22264163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs |
E550304
|
entity |
| Predicate | hasNeutralAlternative |
P147597
|
FINISHED |
| Object | Ms |
—
|
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: Ms | Statement: [Mrs, hasNeutralAlternative, Ms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeutralAlternative Context triple: [Mrs, hasNeutralAlternative, Ms]
-
A.
usesNeutral
Indicates that one entity employs or applies something in a neutral, unbiased, or non-aligned manner toward another entity or context.
-
B.
hasAlternativeHypothesis
Indicates that an entity is associated with another entity that serves as a different or competing hypothesis to explain the same phenomenon or data.
-
C.
hasAlternativeReferent
Indicates that an entity can also be referred to or identified by an alternative name, label, or reference.
-
D.
hasAlternativeVocalization
Indicates that an entity has another valid way it can be vocalized or pronounced, distinct from its primary or standard vocalization.
-
E.
hasAlternativeMedium
Indicates that an entity is available, expressed, or presented in another medium or format as an alternative to its primary one.
- F. None of above. chosen
Provenance (4 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141ba5c9481909e24067133918ae2 |
completed | April 28, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:39 p.m.