Triple
T7142207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noah Segan |
E166472
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Noah |
E502314
|
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: Noah | Statement: [Noah Segan, givenName, Noah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noah Context triple: [Noah Segan, givenName, Noah]
-
A.
Noah
Noah is a central prophet in the Abrahamic traditions, best known for building an ark to survive a divinely sent flood meant to cleanse the world.
-
B.
Noah
Noah is a 2014 biblical epic film directed by Darren Aronofsky, in which Russell Crowe stars as the titular patriarch tasked with building an ark to survive a divinely sent flood.
-
C.
Noah
chosen
Noah is a masculine given name of Hebrew origin meaning "rest" or "comfort," widely used in many cultures and popular in contemporary English-speaking countries.
-
D.
Ham (Noah film character)
Ham is one of Noah’s sons in the 2014 biblical epic film "Noah," portrayed as a conflicted young man struggling with loyalty, faith, and his place within his family during the Great Flood.
-
E.
Ojani Noa
Ojani Noa is a Cuban former waiter, model, and actor best known for being Jennifer Lopez’s first husband.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e779ace48190be9c33750e60a79e |
completed | March 27, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a3502ed88190ac378a93891c8d9e |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:45 p.m.