Triple
T10217026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Leinster |
E242470
|
entity |
| Predicate | wroteForPublication |
P11775
|
FINISHED |
| Object | Argosy |
E45663
|
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: Argosy | Statement: [Murray Leinster, wroteForPublication, Argosy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argosy Context triple: [Murray Leinster, wroteForPublication, Argosy]
-
A.
Argosy
chosen
Argosy is a British pulp magazine best known for publishing adventure and genre fiction during the early to mid-20th century.
-
B.
Whydah
Whydah was a prominent West African coastal port city that became a major center for the Atlantic slave trade during the era of the Kingdom of Dahomey.
-
C.
The Fortune
The Fortune is a 1975 American comedy film directed by Mike Nichols and best known for starring Jack Nicholson and Warren Beatty as inept con men in a 1920s screwball caper.
-
D.
Argos
Argos is one of the oldest continuously inhabited cities in Greece, located in the Peloponnese and historically significant as a major center of ancient Greek civilization.
-
E.
Argos
Argos is a major UK-based catalogue and online retailer known for offering a wide range of household goods, electronics, toys, and more through both physical stores and digital channels.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa6e544c8190961cdd7f1fbe24e6 |
completed | April 6, 2026, 12:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a8142f948190b19e3c1f70f6430f |
completed | April 8, 2026, 7:10 p.m. |
Created at: April 6, 2026, 11:06 a.m.