Triple
T6339420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura |
E142585
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Laurel |
E372101
|
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: Laurel | Statement: [Laura, hasVariant, Laurel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurel Context triple: [Laura, hasVariant, Laurel]
-
A.
Laurel
Laurel is a small city in Maryland known for its suburban character and location between Washington, D.C. and Baltimore.
-
B.
Laurel
chosen
Laurel is a feminine given name of English origin, derived from the laurel tree traditionally associated with honor and victory.
-
C.
Warley
Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
-
D.
Roscoe
"Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
-
E.
Roscoe
Roscoe is a rural unincorporated community located in Coweta County, Georgia, known for its quiet residential character and countryside setting.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654fb774819087bffb8b966a790a |
completed | March 22, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604352f148190b5accc28462256ad |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.