Triple
T38243342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Republican (early political affiliation) |
E1013826
|
entity |
| Predicate | narrowerThan |
P190203
|
FINISHED |
| Object | general 19th-century republicanism |
—
|
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: general 19th-century republicanism | Statement: [Red Republican (early political affiliation), narrowerThan, general 19th-century republicanism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrowerThan Context triple: [Red Republican (early political affiliation), narrowerThan, general 19th-century republicanism]
-
A.
smallerThan
Indicates that one entity has a strictly lesser size, dimension, or magnitude than another entity.
-
B.
isNarrow
Indicates that something has a small width or limited breadth relative to a reference or context.
-
C.
hasNarrowestWidth
Indicates that one entity has the smallest width dimension compared to a specified set of entities or alternatives.
-
D.
weakerThan
Indicates that one entity has less strength, power, or effectiveness than another entity.
-
E.
largerThan
Indicates that one entity has a greater size, extent, or magnitude than another entity.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc3321ef081908023590ba70ba0cf |
completed | May 7, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fdc6e08190b05e894c59481a0d |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc330b4288190858b49d986160706 |
completed | May 7, 2026, 4:52 p.m. |
Created at: May 3, 2026, 4:30 p.m.