Triple
T19731448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Karenina |
E473862
|
entity |
| Predicate | meetsLoverAt |
P62310
|
FINISHED |
| Object | train station |
—
|
LITERAL 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: train station | Statement: [Anna Karenina, meetsLoverAt, train station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsLoverAt Context triple: [Anna Karenina, meetsLoverAt, train station]
-
A.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
B.
meetsTo
chosen
Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
-
C.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
D.
meetsBetween
Indicates that one entity meets or encounters another at some point between two specified reference points or times.
-
E.
meetsVia
Indicates that two entities come into contact or interact with each other through a specified intermediary medium, channel, or mechanism.
- F. None of above.
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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649fd18148190a6e85b2be0069dde |
completed | April 20, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.