Triple
T8595183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Emily Hardy |
E203526
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Marian |
E62460
|
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: Marian | Statement: [Mrs. Emily Hardy, child, Marian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marian Context triple: [Mrs. Emily Hardy, child, Marian]
-
A.
Marian
chosen
Marian is a given name of Latin origin commonly used in various European countries for both males and females.
-
B.
Marian
Marian is a small rural town and sugar-growing community in Queensland, Australia, located within the Mackay Region.
-
C.
Mary Desha
Mary Desha was an American educator and civic leader best known as one of the four co-founders of the patriotic lineage organization Daughters of the American Revolution.
-
D.
Elizabeth of the Trinity
Elizabeth of the Trinity was a French Discalced Carmelite nun and mystic, known for her profound writings on contemplative prayer and the indwelling of the Holy Trinity.
-
E.
Joan
Joan is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
- 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_69ca832a7f108190b4e4f5648abf4aa2 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46c76fd48190ae67b660c5b8e29f |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea8c9fcc48190ba20c85e226ef5f3 |
completed | April 2, 2026, 5:35 p.m. |
Created at: March 30, 2026, 6:23 p.m.