Triple
T11571690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristin Nelson |
E274401
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Harmon |
E449258
|
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: Harmon | Statement: [Kristin Nelson, familyName, Harmon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harmon Context triple: [Kristin Nelson, familyName, Harmon]
-
A.
Harmon
Harmon was the original name of the railway station now known as Croton–Harmon, a major commuter and intercity rail hub in New York's Hudson Valley.
-
B.
Harmon
Harmon is the middle name of Horace Harmon Lurton, an American jurist who served as an Associate Justice of the U.S. Supreme Court in the early 20th century.
-
C.
Harmon
chosen
Harmon is the maiden surname of Ellen G. White, a co-founder and prophetic figure of the Seventh-day Adventist Church.
-
D.
Haro
Haro is a historic town in Spain’s La Rioja region, renowned for its wineries and annual wine festival.
-
E.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd6913881908becf188c0a7a275 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e713d18ccc8190a63256c3cc1c2f59 |
completed | April 21, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:38 p.m.