Triple
T1795331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harper Lee |
E39590
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nelle |
E13447
|
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: Nelle | Statement: [Harper Lee, givenName, Nelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelle Context triple: [Harper Lee, givenName, Nelle]
-
A.
Nell
chosen
Nell is a feminine given name, often used as a diminutive of names like Eleanor or Helen.
-
B.
Nesta
Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
-
C.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
D.
Nene
Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
-
E.
Nese
Nese is an endangered Oceanic language spoken by a small community on the island of Malakula in Vanuatu.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa653daa0c8190a5d96c20c8a0af15 |
completed | March 6, 2026, 5:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5d49d7481909dcb5cc54b92e3cc |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:32 p.m.