Triple
T16333335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beatrice Straight |
E396610
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Network |
E300953
|
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: Network | Statement: [Beatrice Straight, notableWork, Network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Network Context triple: [Beatrice Straight, notableWork, Network]
-
A.
Network
Network is a National Hunt stallion best known as the sire of top-class jump racehorses, including the champion chaser Sprinter Sacre.
-
B.
Network
chosen
Network is a 1976 satirical drama film directed by Sidney Lumet that critiques television news and media sensationalism.
-
C.
NETWORK
NETWORK is the radio callsign used by Network Aviation, an Australian regional airline operating charter and scheduled services.
-
D.
Network World
Network World is a technology-focused publication that covers computer networking news, analysis, and trends for IT professionals.
-
E.
Networker
Networker is a family of electric and diesel multiple-unit trains used on suburban and regional rail services in southeast England.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e1da1081909bec6e77e6109dce |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0026173dc081909e00f6647d1f68b3 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:07 a.m.