Triple
T4157593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Theory of Justice |
E91452
|
entity |
| Predicate | setsIn |
P54147
|
FINISHED |
| Object | hypothetical original position of equality |
—
|
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: hypothetical original position of equality | Statement: [A Theory of Justice, setsIn, hypothetical original position of equality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsIn Context triple: [A Theory of Justice, setsIn, hypothetical original position of equality]
-
A.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
B.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
C.
setsInMotion
Indicates initiating movement or causing an entity to begin moving or proceeding from a state of rest.
-
D.
set
Indicates that an entity places, positions, or establishes another entity into a particular state, configuration, or location.
-
E.
sharesSetsWith
Indicates that two entities have one or more sets in common, or participate in at least one identical set.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0320775c8190b90d80f512060f1c |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:44 p.m.