Triple
T3864915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rene Auberjonois |
E91827
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Archer |
E345559
|
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: Archer | Statement: [Rene Auberjonois, appearedIn, Archer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Archer Context triple: [Rene Auberjonois, appearedIn, Archer]
-
A.
Archer
chosen
Archer is an animated adult comedy series known for its irreverent spy-themed humor and distinctive visual style, airing on the FX network.
-
B.
Archer
Archer is an English occupational surname historically given to bowmen and now borne by various notable individuals across fields such as music, politics, and sports.
-
C.
Flecher
Flecher is a variant spelling of the surname Fletcher, which traditionally refers to a maker or seller of arrows.
-
D.
Arrow
Arrow is a popular American superhero television series based on the DC Comics character Green Arrow, known for launching the interconnected "Arrowverse" franchise.
-
E.
Arrow
Arrow is the English translation of "Freccia," the nickname of the Italian World War II fighter aircraft Fiat G.50.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3a253c81909df7dc0422ff7989 |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5123e5e008190a89bb226a7de55ec |
completed | March 14, 2026, 7:46 a.m. |
Created at: March 9, 2026, 3:19 p.m.