Triple
T16911106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willard Brown |
E410195
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Willard |
E95032
|
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: Willard | Statement: [Willard Brown, givenName, Willard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willard Context triple: [Willard Brown, givenName, Willard]
-
A.
Willard
chosen
Willard is a masculine given name of Old English origin meaning "resolute" or "strong-willed."
-
B.
Willard
Willard is a coastal neighborhood in South Portland, Maine, known for its sandy beach and residential seaside character.
-
C.
Willard
Willard is a small village in central New Mexico, United States, known for its rural character and location on the high plains.
-
D.
Orrin
Orrin is a masculine given name most notably borne by long-serving U.S. Senator Orrin Hatch of Utah.
-
E.
Willard Louis
Willard Louis was an American character actor of the silent film era, known for his supporting roles in numerous comedies and dramas of the 1910s and 1920s.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3ca0c481909ff361ccf4a922e3 |
completed | April 18, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfd0ff2881908686678daab46664 |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 10, 2026, 5:30 a.m.