Triple
T1618393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gordon E. Moore |
E34772
|
entity |
| Predicate | hasMiddleName |
P143
|
FINISHED |
| Object | Earle |
E34772
|
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: Earle | Statement: [Gordon E. Moore, hasMiddleName, Earle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Earle Context triple: [Gordon E. Moore, hasMiddleName, Earle]
-
A.
Earle
chosen
Earle is the middle name of Gordon E. Moore, the co-founder of Intel and originator of Moore’s Law.
-
B.
Earl
An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
-
C.
Everette
Everette is the given first name of E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
-
D.
Cloyce
Cloyce is a surname most notably associated with Sarah Cloyce, one of the women accused during the Salem witch trials in 17th-century Massachusetts.
-
E.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909addb348190a80a97422efcaa63 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51cf7b7c8190847ab6795fb5613b |
completed | March 8, 2026, 10:39 a.m. |
Created at: March 4, 2026, 7:28 p.m.