Triple
T26557077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Dravot |
E666138
|
entity |
| Predicate | relationshipToPeacheyCarnehan |
P197288
|
FINISHED |
| Object | friend |
—
|
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: friend | Statement: [Daniel Dravot, relationshipToPeacheyCarnehan, friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPeacheyCarnehan Context triple: [Daniel Dravot, relationshipToPeacheyCarnehan, friend]
-
A.
relationshipToHarveyCheyneJr
Indicates the specific familial, social, or professional relationship that an entity has to Harvey Cheyne Jr.
-
B.
relationshipToCarolPeletier
Indicates the specific familial, social, or interpersonal connection an entity has to Carol Peletier.
-
C.
relationshipTypeWithSidney Cochran
Indicates the specific nature or category of the relationship that an entity has with Sidney Cochran.
-
D.
relationshipTypeWithShelbyCarpenter
Indicates the specific nature or category of relationship that an entity has with Shelby Carpenter.
-
E.
relationshipToPawneeNation
Indicates the specific type of familial, legal, historical, or political relationship that an entity has with the Pawnee Nation.
- 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_69ee9cf7e94481909f0d556b36e43572 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
| PDg | Predicate description generation | batch_69fe86c98d688190a99d5dcb14e2dc95 |
completed | May 9, 2026, 12:58 a.m. |
Created at: April 27, 2026, 1:50 a.m.