Triple
T2707014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veritas |
E59364
|
entity |
| Predicate | hasWord |
P35
|
FINISHED |
| Object | Veritas |
E104
|
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: Veritas | Statement: [Veritas, hasWord, Veritas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veritas Context triple: [Veritas, hasWord, Veritas]
-
A.
Veritas
chosen
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
B.
Siris
Siris is a philosophical work by George Berkeley that explores metaphysics, theology, and the medicinal virtues of tar-water through a chain of reflective questions and arguments.
-
C.
Verily
Verily is a life sciences and healthcare technology company under Alphabet Inc. that focuses on using data and advanced tools to improve health outcomes.
-
D.
Soter
Soter is a Greek term meaning "savior" or "deliverer," often used as a title for deities or revered figures who provide salvation or protection.
-
E.
Didymus
Didymus is another name for the Apostle Thomas, one of Jesus Christ’s twelve original disciples in the New Testament.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda725f24819090e8d936b3d2d5bc |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf7c22a4819096ff9effe9e0d77d |
completed | March 10, 2026, 5:43 a.m. |
Created at: March 6, 2026, 9:55 p.m.