Triple
T11051984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Ruttenberg |
E261277
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Joseph |
E77392
|
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: Joseph | Statement: [Joseph Ruttenberg, givenName, Joseph]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joseph Context triple: [Joseph Ruttenberg, givenName, Joseph]
-
A.
Joseph
chosen
Joseph is a common masculine given name of Hebrew origin, traditionally interpreted to mean "He will add" or "God increases."
-
B.
Joseph
Joseph is a revered prophet in Islamic tradition, known for his exemplary patience, prophetic dreams, and moral integrity as recounted in Surah Yusuf of the Qur’an.
-
C.
Joseph
Joseph is the given name of the renowned British Romantic landscape painter J. M. W. Turner.
-
D.
Joseph
Joseph, also known as Barnabas, was an early Christian disciple and companion of the Apostle Paul, recognized for his missionary work and role in the spread of Christianity.
-
E.
Joseph
Joseph is the given name of Joseph Rucker Lamar, an American lawyer and Associate Justice of the U.S. Supreme Court in the early 20th century.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7986c0df88190b29d71db5538450a |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3aa1c2d9c8190959e28ccef4e0f6d |
completed | April 18, 2026, 3:58 p.m. |
Created at: April 8, 2026, 9:26 p.m.