Triple
T691011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Messier |
E13391
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mark |
E1581
|
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: Mark | Statement: [Mark Messier, givenName, Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Context triple: [Mark Messier, givenName, Mark]
-
A.
Mark
chosen
Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
-
B.
Marc
Marc is the given name of Marc Andreessen, the influential American entrepreneur, software engineer, and venture capitalist known for co-creating the Mosaic web browser and co-founding Netscape and Andreessen Horowitz.
-
C.
Jonathan
Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
-
D.
Jeremy
Jeremy is one of the central male protagonists in the romantic comedy film "Think Like a Man," which follows a group of men whose relationships are upended when their partners start using advice from Steve Harvey’s dating book.
-
E.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0aebde88190a49d421477713103 |
completed | March 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a637514c9081909938d0801f071fea |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:36 p.m.