Triple
T2223923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Marshall Harlan |
E48604
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Harlan |
E193721
|
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: Harlan | Statement: [John Marshall Harlan, familyName, Harlan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harlan Context triple: [John Marshall Harlan, familyName, Harlan]
-
A.
Harlan
chosen
Harlan is a masculine given name of English origin, historically associated with figures such as U.S. Chief Justice Harlan F. Stone.
-
B.
De Witt
De Witt is a Dutch surname most famously associated with Johan de Witt, a prominent 17th-century statesman of the Dutch Republic.
-
C.
Andrew Harlan
Andrew Harlan is the time-manipulating Technician protagonist of Isaac Asimov’s science fiction novel "The End of Eternity."
-
D.
Daggett
Daggett is a small unincorporated desert community in San Bernardino County, California, historically known as a railroad and mining town along major transportation routes.
-
E.
Burwell
Burwell is an English surname historically associated with several notable figures and families in Britain and the United States.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03d1df88190950c691a4c246bd1 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6562c9448190b53c068c900bf0bf |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:47 p.m.