Triple
T28773629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarasis Kodisa Rousombladadiotes |
E726475
|
entity |
| Predicate | predecessorAs |
P97
|
FINISHED |
| Object | Leo II |
—
|
NE NERFINISHED |
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: Leo II | Statement: [Tarasis Kodisa Rousombladadiotes, predecessorAs, Leo II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorAs Context triple: [Tarasis Kodisa Rousombladadiotes, predecessorAs, Leo II]
-
A.
predecessor
chosen
Indicates that one entity comes before another in an ordered sequence or succession.
-
B.
predecessorName
Indicates that the value is the name of an entity that directly precedes another in an ordered sequence or lineage.
-
C.
predecessorFamily
Indicates that one family is the earlier or ancestral family from which another family descends or follows.
-
D.
predecessorInSuit
Indicates that one item directly precedes another in an ordered sequence within the same suit or category.
-
E.
predecessorUsedFrom
Indicates that something was used or derived from a preceding version, state, or entity that came before it.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 28, 2026, 6:16 a.m.