Triple
T8030865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Nicholls |
E186973
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Us |
E365177
|
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: Us | Statement: [David Nicholls, notableWork, Us]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Us Context triple: [David Nicholls, notableWork, Us]
-
A.
Us
Us is a 2019 horror film written and directed by Jordan Peele that explores themes of identity and duality through a family's terrifying encounter with their doppelgängers.
-
B.
Us
chosen
"Us" is a soulful pop ballad by British singer-songwriter James Bay that explores themes of hope, connection, and emotional vulnerability.
-
C.
US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
-
D.
US
US is the commonly used abbreviation for the University of Seville, a major public research university located in Seville, Spain.
-
E.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3eef921081908d0ea21f142c175a |
completed | March 31, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63c911c081909751b614966d986c |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:22 p.m.