Triple
T2883797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Barrett Browning |
E59458
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Barrett |
E199811
|
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: Barrett | Statement: [Elizabeth Barrett Browning, familyName, Barrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrett Context triple: [Elizabeth Barrett Browning, familyName, Barrett]
-
A.
Barrett
chosen
Barrett is a common English and Irish surname borne by numerous notable individuals across politics, law, sports, and the arts.
-
B.
Barret Zoph
Barret Zoph is a machine learning researcher known for his work on neural architecture search and contributions to deep learning at Google Brain.
-
C.
Barnett
Barnett is a masculine given name most notably associated with the influential American abstract expressionist painter Barnett Newman.
-
D.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
E.
Bartel
Bartel is the given name of Bartel Leendert van der Waerden, a prominent Dutch mathematician known for his work in algebra and number theory.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe02e0ec48190b969ed921d179560 |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b03167d7dc819093e91e0d42f3de6f |
completed | March 10, 2026, 2:57 p.m. |
Created at: March 6, 2026, 10:03 p.m.