Triple
T14722702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Black Legend |
E345854
|
entity |
| Predicate | exaggerates |
P115523
|
FINISHED |
| Object | Spanish atrocities |
—
|
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: Spanish atrocities | Statement: [Spanish Black Legend, exaggerates, Spanish atrocities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exaggerates Context triple: [Spanish Black Legend, exaggerates, Spanish atrocities]
-
A.
excites
Indicates that one entity causes another entity to become excited, stimulated, or activated, typically by increasing its energy or arousal level.
-
B.
glorifies
Indicates that one entity praises, exalts, or represents another in an admiring or honor-enhancing way.
-
C.
moreExpressiveThan
Indicates that one entity conveys ideas, emotions, or information with greater richness, nuance, or clarity than another.
-
D.
negates
Indicates that one entity denies, contradicts, or renders false the assertion, state, or effect expressed by another.
-
E.
correctsAberration
Indicates that one entity counteracts, fixes, or compensates for an error, flaw, or deviation present in 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25d56fc8190871873ca55d49272 |
completed | April 14, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69de657e174481909da0437556334a04 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716d3aac8190aaa6dc1f099b86e8 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:29 a.m.