Triple
T28923928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Claythorne |
E733592
|
entity |
| Predicate | invitedToIslandBy |
P96638
|
FINISHED |
| Object |
U. N. Owen
U. N. Owen is the mysterious, unseen host and orchestrator of the events in Agatha Christie's novel "And Then There Were None," whose name is a pun on "unknown."
|
E1843740
|
NE FINISHED |
How this triple was built (3 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: U. N. Owen | Statement: [Vera Claythorne, invitedToIslandBy, U. N. Owen]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: U. N. Owen Triple: [Vera Claythorne, invitedToIslandBy, U. N. Owen]
Generated description
U. N. Owen is the mysterious, unseen host and orchestrator of the events in Agatha Christie's novel "And Then There Were None," whose name is a pun on "unknown."
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: invitedToIslandBy Context triple: [Vera Claythorne, invitedToIslandBy, U. N. Owen]
-
A.
isInvited
Indicates that one entity has extended an invitation to another entity to participate in or attend something.
-
B.
invitesToLocation
chosen
Indicates that one entity extends an invitation to another entity to go to or be present at a specific location.
-
C.
invitesParticipationOf
Indicates that one entity actively requests or encourages another entity to take part in an activity, event, or process.
-
D.
grantedIsland
Indicates that an authority has formally given control or ownership of an island to a recipient.
-
E.
hasIsland
Indicates that one entity possesses, contains, or includes an island as part of its domain, territory, or structure.
- F. None of above.
Provenance (6 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_69f05b0a5cc0819094828367ae204b70 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b1d1c688190b035919575bb2164 |
completed | May 2, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2505a0ecb4819098187b0b3f1a74a6 |
completed | June 7, 2026, 5:46 a.m. |
| NEDg | Description generation | batch_6a250a2a72cc81909f3db982d72e0aea |
completed | June 7, 2026, 6:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a250bf193848190b0e106fca76e3e3e |
completed | June 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:22 a.m.