Triple
T5599491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Senesky |
E147079
|
entity |
| Predicate | draftLeague |
P2643
|
FINISHED |
| Object | BAA |
E3927
|
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: BAA | Statement: [George Senesky, draftLeague, BAA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BAA Context triple: [George Senesky, draftLeague, BAA]
-
A.
BAA
chosen
BAA is the acronym for the Basketball Association of America, the professional basketball league that later merged to form today’s National Basketball Association (NBA).
-
B.
BAAS
BAAS is the acronym commonly used for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
-
C.
BBN
BBN is the early-universe process that produced the lightest elements—mainly hydrogen, helium, and small amounts of lithium—within the first few minutes after the Big Bang.
-
D.
BAF
BAF is the service number prefix used to identify personnel of the Belgian Air Component (Belgian Air Force).
-
E.
BAW
BAW is the ICAO airline designator used in aviation to identify British Airways flights and operations.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020d936dc8190a2e599f1df9fdd91 |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0287139508190aa646918228cfdc0 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:38 p.m.