Triple
T7376029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wade Boggs |
E170125
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wade |
E103612
|
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: Wade | Statement: [Wade Boggs, givenName, Wade]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wade Context triple: [Wade Boggs, givenName, Wade]
-
A.
Wade
chosen
Wade is a common English surname borne by numerous notable individuals across fields such as law, sports, and the arts.
-
B.
Dwane
Dwane is a masculine given name most notably borne by NBA coach Dwane Casey.
-
C.
Kaavia James Union Wade
Kaavia James Union Wade is the daughter of actress Gabrielle Union and former NBA star Dwyane Wade, known publicly from birth through her parents’ high-profile social media presence.
-
D.
Wade Ripple
Wade Ripple is a water-based character in Pixar's animated film "Elemental," known for his emotional sensitivity and relationship with the fiery Ember.
-
E.
Warrick Brown
Warrick Brown is a fictional crime scene investigator and forensic analyst on the television series "CSI: Crime Scene Investigation."
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a780f88190abf11994e307b6ad |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802d15a8481908e43701459607276 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:07 p.m.