Triple
T3452071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maureen Stapleton |
E72814
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maureen |
E213961
|
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: Maureen | Statement: [Maureen Stapleton, givenName, Maureen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maureen Context triple: [Maureen Stapleton, givenName, Maureen]
-
A.
Maureen
chosen
Maureen is a feminine given name of Irish origin, commonly used in English-speaking countries.
-
B.
Maryanne
Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
-
C.
Marjorie
Marjorie is a feminine given name of French origin that has been widely used in English-speaking countries.
-
D.
Madelaine
Madelaine is a character in the Danish crime thriller film "The Salvation."
-
E.
Dorys Madden
Dorys Madden is best known as the wife of Basketball Hall of Famer Julius "Dr. J" Erving.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbaa2f5ec81909ced93c01e8fe38b |
completed | March 8, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b367ff05a08190a0c4df5ebfb9741d |
completed | March 13, 2026, 1:27 a.m. |
Created at: March 8, 2026, 3:16 p.m.