Triple
T15946118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Franz |
E386686
|
entity |
| Predicate | primaryActivityInPlot |
P88311
|
FINISHED |
| Object | negotiating the price of old furniture |
—
|
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: negotiating the price of old furniture | Statement: [Walter Franz, primaryActivityInPlot, negotiating the price of old furniture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryActivityInPlot Context triple: [Walter Franz, primaryActivityInPlot, negotiating the price of old furniture]
-
A.
primaryFunctionInPlot
chosen
Indicates the main narrative role or purpose that an entity serves within the plot of a story.
-
B.
primaryEngagement
Indicates the main or most significant interaction, involvement, or relationship that an entity has with another entity or activity.
-
C.
primaryIntent
Indicates the main purpose, goal, or motivation underlying an action, event, or relationship among entities.
-
D.
primaryInteraction
Indicates the main or most significant interaction occurring between the involved entities.
-
E.
primarySignificance
Indicates that something has the greatest importance, relevance, or impact among a set of related things or factors.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.