Triple
T9437632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy Mills |
E227553
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Mills |
E39389
|
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: Mills | Statement: [Wendy Mills, hasSurname, Mills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mills Context triple: [Wendy Mills, hasSurname, Mills]
-
A.
Mills
chosen
Mills is a common English surname borne by numerous notable individuals across fields such as music, politics, sports, and academia.
-
B.
The Mills
The Mills is a portfolio of large outlet and value-oriented shopping malls in the United States, known for combining retail, dining, and entertainment under the ownership of Simon Property Group.
-
C.
Milles
Milles is a surname and variant of "Mills" that appears in English-speaking contexts.
-
D.
The Mill
"The Mill" is a dark, psychologically intense narrative poem by Edwin Arlington Robinson that explores themes of despair, miscommunication, and tragic misunderstanding within a miller’s family.
-
E.
Weeks Mills
Weeks Mills is a small village within the town of China in Kennebec County, central Maine.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7edff5e881909b72976e8909ba4b |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1225345488190a1fee54f6feb321d |
completed | April 4, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:50 p.m.