Triple
T12777190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Hartnett |
E305407
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Hartnett |
E47461
|
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: Hartnett | Statement: [Joseph Hartnett, hasSurname, Hartnett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hartnett Context triple: [Joseph Hartnett, hasSurname, Hartnett]
-
A.
Hartnett
chosen
Hartnett is a surname most prominently associated with American actor Josh Hartnett, known for his film and television roles since the late 1990s.
-
B.
Robert Hartnett
Robert Hartnett is an individual notable enough to be specifically cited as a bearer of the surname Hartnett.
-
C.
Hillegas
Hillegas is a surname most notably associated with Michael Hillegas, the first Treasurer of the United States.
-
D.
Haardt
Haardt is a district of Neustadt an der Weinstraße in Rhineland-Palatinate, Germany, known for its scenic location along the German Wine Route and proximity to the Palatinate Forest.
-
E.
Hayne
Hayne is a surname most notably associated with Robert Y. Hayne, a prominent 19th-century American politician and orator from South Carolina.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e595e008190b42dff3012d17d66 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f685013e0481908db09302a2ced207 |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:29 p.m.