Triple
T6048188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tore |
E134719
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Torey |
E564521
|
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: Torey | Statement: [Tore, relatedName, Torey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torey Context triple: [Tore, relatedName, Torey]
-
A.
Torey
chosen
Torey is a given name, typically used as a variant of names like Tore or Tory.
-
B.
Laurie
Laurie is a character from the horror film "Night Monster," involved in the eerie and suspenseful events surrounding the mysterious killings at the Ingston estate.
-
C.
Laurie
Laurie is a charming, wealthy, and impulsive young man who becomes a close friend and would-be suitor to the March sisters in Louisa May Alcott’s novel "Little Women."
-
D.
Tanya
Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
-
E.
Tanya
Tanya is a common diminutive form of the female given name Tatyana, used in various Slavic and English-speaking contexts.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056f387cc8190920b846995761aec |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d01aa208190a9c630780f5b9851 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:09 p.m.