Triple
T10801735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Health Solutions |
E254852
|
entity |
| Predicate | hasParentCompanyTicker |
P21787
|
FINISHED |
| Object | AON |
E254847
|
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: AON | Statement: [Health Solutions, hasParentCompanyTicker, AON]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AON Context triple: [Health Solutions, hasParentCompanyTicker, AON]
-
A.
AON
AON is the National Rail station code for Alton railway station in Hampshire, England.
-
B.
AON
chosen
AON is a global professional services firm specializing in risk management, insurance and reinsurance brokerage, and human capital consulting.
-
C.
AO
AO was the foreign organization branch of the Nazi Party (NSDAP), responsible for coordinating and overseeing party activities among Germans living abroad.
-
D.
AO
AO is the two-letter ISO 3166-1 alpha-2 country code representing Angola in international standards and systems.
-
E.
AO
AO is the common abbreviation for Agent Orange, a highly toxic herbicide and defoliant used by the U.S. military during the Vietnam War that caused widespread environmental damage and severe health effects.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7336dedec819099bd302c5d213dba |
completed | April 9, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de850209ac8190a7bf3a6d429d1217 |
completed | April 14, 2026, 6:18 p.m. |
Created at: April 8, 2026, 9:18 p.m.