Triple
T158601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King David |
E3231
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Abigail |
E29086
|
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: Abigail | Statement: [King David, spouse, Abigail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abigail Context triple: [King David, spouse, Abigail]
-
A.
Abigail
chosen
Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
-
B.
Margaret
Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
-
C.
Louise
Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
-
D.
Nancy
Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
-
E.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2583169a0819081b658882e5bc452 |
completed | Feb. 28, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a37656c324819099761a1d5ae00637 |
completed | Feb. 28, 2026, 11:12 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.