Triple
T16423675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alison Pill |
E398883
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pill |
E1154327
|
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: Pill | Statement: [Alison Pill, familyName, Pill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pill Context triple: [Alison Pill, familyName, Pill]
-
A.
Pill
Pill is a small village in North Somerset, England, situated near the River Avon and close to the town of Portishead.
-
B.
Pill
chosen
Pill is an American rapper known for his association with Rick Ross’s Maybach Music Group and his early contributions to the Atlanta hip-hop scene.
-
C.
Piller
Piller is a surname most notably associated with Michael Piller, a prominent American television writer and producer known for his influential work on the Star Trek franchise.
-
D.
Pille
Pille is the talking football character that served as the sidekick to Goleo VI, the official mascot of the 2006 FIFA World Cup in Germany.
-
E.
Pililla
Pililla is a rural lakeside municipality in the province of Rizal in the Philippines, known for its wind farm and scenic views of Laguna de Bay.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f911b88190b19de52a1f700af8 |
completed | April 18, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c70aaa08190bf88210c0b491fc1 |
completed | May 10, 2026, 8:06 a.m. |
Created at: April 10, 2026, 5:09 a.m.