Triple
T14858736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Dane |
E349431
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Dane |
E390474
|
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: Dane | Statement: [Nathan Dane, familyName, Dane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dane Context triple: [Nathan Dane, familyName, Dane]
-
A.
Dane
chosen
A Dane is a person from Denmark, typically associated with Danish nationality, culture, and language.
-
B.
Dane Henry
Dane Henry is a film editor best known for his work on the acclaimed rock climbing documentary "The Dawn Wall."
-
C.
Dane Charles
Dane Charles is a songwriter best known for co-writing the track "Bring Me Love."
-
D.
Luke Danes
Luke Danes is a gruff but kind-hearted diner owner in the television series "Gilmore Girls," known for his close relationship with Lorelai Gilmore and his central role in the small-town community of Stars Hollow.
-
E.
Dan
Dan is a character in the play "Clybourne Park," representing a contemporary figure who uncovers the neighborhood’s buried history and helps connect past events to present-day tensions.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe650a43bc8190b836fe690d2a3c71 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:54 a.m.