Triple
T1573752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Gustav Fleischer |
E33600
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Carl |
E2910
|
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: Carl | Statement: [Carl Gustav Fleischer, givenName, Carl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carl Context triple: [Carl Gustav Fleischer, givenName, Carl]
-
A.
Carl
chosen
Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
-
B.
Carl
Carl is the given name of Charles I Louis, the 17th-century Elector Palatine of the Rhine in the Holy Roman Empire.
-
C.
Charlie
Charlie was the third nuclear test in the U.S. Operation Crossroads series, planned as an underwater detonation to study the effects of nuclear weapons on naval vessels.
-
D.
Charlie
Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
-
E.
Harold
Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908bcd87881908b911314a30dd327 |
completed | March 5, 2026, 4:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4028bc5881909dbe847229dd63bb |
completed | March 8, 2026, 9:23 a.m. |
Created at: March 4, 2026, 7:27 p.m.