Triple
T18026763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wayne as Tom Doniphon |
E431271
|
entity |
| Predicate | relationshipToRansomStoddard |
P129509
|
FINISHED |
| Object | reluctant ally |
—
|
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: reluctant ally | Statement: [John Wayne as Tom Doniphon, relationshipToRansomStoddard, reluctant ally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRansomStoddard Context triple: [John Wayne as Tom Doniphon, relationshipToRansomStoddard, reluctant ally]
-
A.
relationshipToHowardStambler
Indicates a specified type of relationship or connection that an entity has to Howard Stambler.
-
B.
relationshipToStanley
Indicates the specific type of personal or social relationship an entity has with Stanley.
-
C.
relationshipToLambertStrether
Indicates the specific type of personal or social relationship that an entity has to Lambert Strether.
-
D.
relationshipTypeWith Mona Stangley
Indicates the specific type or nature of relationship that an entity has with Mona Stangley.
-
E.
relationshipToTramp
Indicates that one entity has a specified type of relationship or connection to a tramp (a vagrant or homeless person).
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c7be308190af0d77c0df6d94ce |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:24 a.m.