Triple
T31173089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Heidegger |
E794665
|
entity |
| Predicate | relationshipToElixir |
P207368
|
FINISHED |
| Object | refuses to drink the elixir himself |
—
|
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: refuses to drink the elixir himself | Statement: [Dr. Heidegger, relationshipToElixir, refuses to drink the elixir himself]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToElixir Context triple: [Dr. Heidegger, relationshipToElixir, refuses to drink the elixir himself]
-
A.
relationshipToFelix
Indicates the specific type of relationship or connection that an entity has with Felix.
-
B.
relationshipToGodot
Indicates the nature or type of connection an entity has to the work, character, or concept referred to as "Godot."
-
C.
relationshipToElijahBaley
Indicates the nature or type of relationship an entity has with Elijah Baley.
-
D.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
E.
relationshipToKlaatu
Indicates the specific familial, social, or professional relationship that one entity has to the entity named Klaatu.
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:07 p.m.