Triple
T35027086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Skakel |
E1010368
|
entity |
| Predicate | locationOfAllegedCrime |
P184635
|
FINISHED |
| Object | Belle Haven, Greenwich, Connecticut, United States |
E1003497
|
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: Belle Haven, Greenwich, Connecticut, United States | Statement: [Michael Skakel, locationOfAllegedCrime, Belle Haven, Greenwich, Connecticut, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfAllegedCrime Context triple: [Michael Skakel, locationOfAllegedCrime, Belle Haven, Greenwich, Connecticut, United States]
-
A.
allegedAssaultLocation
chosen
Indicates the place where an assault is claimed or reported to have occurred, without asserting that the assault actually happened.
-
B.
positionOnCrime
Indicates a stance, opinion, or policy position that an entity holds regarding crime or crime-related issues.
-
C.
crimeLocation
Indicates that a crime occurred at, or is associated with, a particular location.
-
D.
allegedShooterLocation
Indicates the place where a person is claimed or reported to have carried out a shooting.
-
E.
allegedMisconductLocation
Indicates the place where the alleged misconduct is reported to have occurred.
- F. None of above.
Provenance (4 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37bd25430c8190ae4e4330e9a05028 |
completed | June 21, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.