Triple
T20264509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warren |
E498928
|
entity |
| Predicate | relationshipToSilas |
P106831
|
FINISHED |
| Object | employer |
—
|
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: employer | Statement: [Warren, relationshipToSilas, employer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSilas Context triple: [Warren, relationshipToSilas, employer]
-
A.
relationshipToSilvius
Indicates the nature or type of relational connection an entity has with Silvius.
-
B.
relationshipToSilasMarner
chosen
Indicates the specific familial, social, or emotional connection that one entity has to Silas Marner.
-
C.
relationshipToNaomi
Indicates the specific familial, social, or interpersonal connection that an entity has with Naomi.
-
D.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
E.
relationshipToSophie
Indicates the specific type of personal or social connection that an entity has to Sophie.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674ce27688190b31d7a6c98d3ec5e |
completed | April 20, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.