Triple
T28372686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Good Soldier |
E718674
|
entity |
| Predicate | settingBefore |
P173246
|
FINISHED |
| Object | World War I |
—
|
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: World War I | Statement: [The Good Soldier, settingBefore, World War I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingBefore Context triple: [The Good Soldier, settingBefore, World War I]
-
A.
settingAfter
Indicates that one setting or configuration occurs or is applied after another in a sequence or order.
-
B.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
C.
preparedBefore
Indicates that one entity was prepared or made ready at an earlier time than another entity.
-
D.
preparesFor
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
-
E.
settingAfterEvent
Indicates that a particular setting or state occurs subsequent to, and as a result of or in temporal sequence with, a specified event.
- F. None of above. chosen
Provenance (4 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6b342499c8190b85009a3f0f179e4 |
completed | May 3, 2026, 2:30 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b2a31e008190aacef03c2ebe5787 |
completed | May 3, 2026, 2:27 a.m. |
Created at: April 28, 2026, 1:01 a.m.