Triple
T14709447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Am Not Okay with This |
E345508
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Dina |
E118897
|
NE 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: Dina | Statement: [I Am Not Okay with This, hasCharacter, Dina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dina Context triple: [I Am Not Okay with This, hasCharacter, Dina]
-
A.
Dina
chosen
Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
-
B.
Dina
Dina is a town in Pakistan’s Punjab province, located within the Jhelum District and known as a local commercial and transport hub.
-
C.
Dawnna
Dawnna is a feminine given name, typically considered a modern or alternative spelling of the name Donna.
-
D.
Sheilia
Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
-
E.
Mena
Mena is a masculine given name of Arabic origin, commonly used in Middle Eastern and North African cultures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb9814e0c8190984ac30d276499cc |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf08d59b48190a1ddd2aed6ed756e |
completed | May 8, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:28 a.m.