Triple
T14962799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joey Sagal |
E373104
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sagal |
E1130532
|
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: Sagal | Statement: [Joey Sagal, familyName, Sagal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sagal Context triple: [Joey Sagal, familyName, Sagal]
-
A.
Sagal
chosen
Sagal is a surname most notably associated with a family of American actors and entertainers, including Jean Sagal and her relatives.
-
B.
Sagàs
Sagàs is a small rural municipality in the Berguedà comarca of Catalonia, Spain, known for its agricultural landscape and traditional Catalan countryside.
-
C.
Sagala
Sagala was an important ancient city in the Punjab region, historically known as a major political and cultural center under Indo-Greek rule.
-
D.
Sagiada
Sagiada is a small coastal town in northwestern Greece, near the Albanian border, known for its fishing harbor and views over the Ionian Sea.
-
E.
Ragalna
Ragalna is a small Italian town on the slopes of Mount Etna in Sicily, known for its volcanic landscapes and agricultural traditions.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6d0487c8190b7754af8c5014b37 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969112d8819094e5d81a8ffa3b8a |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:40 a.m.