Triple
T21108415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sassi |
E520111
|
entity |
| Predicate | hasCounterpartIn |
P6587
|
FINISHED |
| Object | other South Asian tragic romances |
—
|
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: other South Asian tragic romances | Statement: [Sassi, hasCounterpartIn, other South Asian tragic romances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCounterpartIn Context triple: [Sassi, hasCounterpartIn, other South Asian tragic romances]
-
A.
hasCounterpart
chosen
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
B.
hasCounterpartNameLanguage
Indicates that an entity’s counterpart (e.g., in another context or system) has a name expressed in a specified language.
-
C.
hasSmallerCounterpart
Indicates that one entity has another entity as its corresponding version that is smaller in size, scale, or magnitude.
-
D.
counterpartRelation
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
E.
hasCounterpartNickname
Indicates that one entity is used as an alternative or counterpart nickname for another entity.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e720ffa998819082db225363ac3b23 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:54 p.m.