Triple
T23245106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zetes |
E581564
|
entity |
| Predicate | traveledOn |
P15183
|
FINISHED |
| Object | Argo |
—
|
NE NERFINISHED |
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: Argo | Statement: [Zetes, traveledOn, Argo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argo Context triple: [Zetes, traveledOn, Argo]
-
A.
Argo
Argo is a 2012 political thriller film directed by Ben Affleck that dramatizes a covert operation to rescue American hostages from Iran during the 1979–1981 crisis.
-
B.
Argo
chosen
Argo is the legendary ship of Greek mythology that carried Jason and the Argonauts on their quest for the Golden Fleece.
-
C.
Argo
Argo is a popular open-source suite of Kubernetes-native tools for running and managing container-native workflows, applications, and continuous delivery pipelines.
-
D.
Argo
Argo is a high-end cocktail bar and restaurant in the Four Seasons Hotel Hong Kong, known for its innovative, globally inspired drinks and contemporary design.
-
E.
Captain Phillips
Captain Phillips is a 2013 biographical thriller film starring Tom Hanks that dramatizes the 2009 hijacking of the Maersk Alabama by Somali pirates.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193ee37c8819091f799506fa532da |
completed | April 29, 2026, 5:15 a.m. |
Created at: April 17, 2026, 4:10 p.m.