Triple
T11405746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marsh & McLennan Companies |
E270234
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Marsh |
E270230
|
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: Marsh | Statement: [Marsh & McLennan Companies, hasSubsidiary, Marsh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marsh Context triple: [Marsh & McLennan Companies, hasSubsidiary, Marsh]
-
A.
Marsh
Marsh is the middle name of William Marsh Rice, the American businessman and philanthropist who founded Rice University in Houston, Texas.
-
B.
Marsh
Marsh is the maiden surname of American country music singer and songwriter Dottie West.
-
C.
Marsh
chosen
Marsh is a global insurance brokerage and risk management firm providing advisory and brokerage services to businesses and individuals worldwide.
-
D.
Marsh
Marsh is a surname most notably associated with Mae Marsh, an American silent film actress renowned for her roles in early 20th-century cinema.
-
E.
Drowned Meadow
Drowned Meadow was the original name of the Long Island village now known as Port Jefferson, a historic harbor community in New York.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014c820c81908538ba4a08e13230 |
completed | April 9, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58d56608481908dbb19daa2abfc0a |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:34 p.m.