Triple
T14780239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hodor |
E347370
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Osha |
E1025501
|
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: Osha | Statement: [Hodor, associatedWith, Osha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osha Context triple: [Hodor, associatedWith, Osha]
-
A.
Osha
Osha is a character portrayed by actress Hannah John-Kamen, known from the science fiction series "Killjoys."
-
B.
Osha
chosen
Osha is a wildling woman and former captive who becomes a loyal protector and caretaker of Bran Stark in the world of Game of Thrones.
-
C.
Otse
Otse is a village located in Botswana’s South-East District, known for its traditional culture and proximity to the capital, Gaborone.
-
D.
Orsa
Orsa is a small locality and municipality in central Sweden known for its forests, lakes, and traditional Dalarna culture.
-
E.
Osanna
Osanna is a choral movement within J.S. Bach’s Mass in B minor, known for its exuberant double-chorus writing and festive character.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9c7cac8190ba900df95e42e318 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0d00d46c8190b6289a9b8511a8fb |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:31 a.m.