Triple
T5320212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Anna Smith |
E121653
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Smith |
E30542
|
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: Smith | Statement: [Mrs. Anna Smith, familyName, Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smith Context triple: [Mrs. Anna Smith, familyName, Smith]
-
A.
Smith
chosen
Smith is a common English surname borne by numerous notable individuals across diverse fields such as politics, arts, sports, and academia.
-
B.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
-
C.
John
John is the given name of John H. Hammond Jr., the influential American record producer and talent scout known for discovering and promoting numerous major jazz, blues, and rock musicians.
-
D.
John
John is the given name of Australian politician John Reid.
-
E.
John
John is the given name of the late Canadian actor and comedian John Candy, known for his roles in films like "Planes, Trains and Automobiles" and "Uncle Buck."
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8574c4b48190a0513ce59eedb564 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18a117d48190a7fb45be0b002f4e |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 1:59 p.m.