Triple
T29607758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belarius |
E754623
|
entity |
| Predicate | relationshipWithCymbeline |
P203468
|
FINISHED |
| Object | former subject |
—
|
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: former subject | Statement: [Belarius, relationshipWithCymbeline, former subject]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithCymbeline Context triple: [Belarius, relationshipWithCymbeline, former subject]
-
A.
relationshipToPriamAndHecuba
Indicates a familial or relational connection that an entity has specifically to both Priam and Hecuba.
-
B.
relationshipToHermia
Indicates the specific type of personal or social relationship that one entity has with Hermia.
-
C.
relationshipToHecuba
Indicates a familial or social connection that an entity has with Hecuba.
-
D.
relationshipToFlorentinoAriza
Indicates the nature of the relationship an entity has with Florentino Ariza.
-
E.
relationshipToKingHamlet
Indicates the specific familial or social relationship an entity has to King Hamlet.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a0189f3f0248190a1b018164d18e6f5 |
completed | May 11, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_6a0187ee0920819097047bb55e1f9506 |
completed | May 11, 2026, 7:40 a.m. |
| PDg | Predicate description generation | batch_6a0189f318c881909c4995203a58a097 |
completed | May 11, 2026, 7:49 a.m. |
Created at: April 28, 2026, 6:26 p.m.