Triple
T23442325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Belcher |
E565436
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Al |
E63325
|
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: Al | Statement: [Bob Belcher, hasRelative, Al]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al Context triple: [Bob Belcher, hasRelative, Al]
-
A.
Al
chosen
Al is a common shortened form of given names such as Albert, Alan, or Alexander.
-
B.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
-
C.
AL
AL is the official United States Postal Service abbreviation for the state of Alabama.
-
D.
AL
AL is the vehicle registration code used on license plates for the Spanish province of Almería.
-
E.
AL
AL is the stock ticker symbol for Air Lease Corporation, a U.S.-based company that purchases commercial aircraft and leases them to airlines worldwide.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64654e88190b530958b27b32412 |
completed | April 29, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c67b583fc8190941de49b824f9c98 |
completed | May 19, 2026, 1:37 p.m. |
Created at: April 17, 2026, 5:51 p.m.