Triple
T7407163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dora Sigerson Shorter |
E170902
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sigerson |
E248023
|
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: Sigerson | Statement: [Dora Sigerson Shorter, familyName, Sigerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sigerson Context triple: [Dora Sigerson Shorter, familyName, Sigerson]
-
A.
Sigerson
chosen
Sigerson is an Irish surname notably borne by members of a literary family, including poet Dora Sigerson Shorter.
-
B.
George Sigerson
George Sigerson was an Irish physician, scientist, translator, and leading figure of the Irish literary revival in the late 19th and early 20th centuries.
-
C.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
D.
O'Herlihy
O'Herlihy is an Irish surname associated with figures in film, television, and the arts.
-
E.
O’Donoghue
O’Donoghue is an Irish surname historically associated with several Gaelic families and clans, particularly in County Kerry and surrounding regions.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f298f2388190afc944c9bc78749a |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8111adbf48190a04df3cec1017b39 |
completed | March 28, 2026, 5:34 p.m. |
Created at: March 27, 2026, 3:10 p.m.