Triple
T16570915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard Oil of New York |
E402580
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | Mobil |
E88383
|
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: Mobil | Statement: [Standard Oil of New York, successor, Mobil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mobil Context triple: [Standard Oil of New York, successor, Mobil]
-
A.
Mobil
chosen
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
B.
Benz
Benz is a German surname most famously associated with automotive pioneer Karl Benz and the Mercedes-Benz brand.
-
C.
Fordon
Fordon is a large residential and industrial district of Bydgoszcz in northern Poland, known for its post-war housing estates and location along the Vistula River.
-
D.
Totota
Totota is a town located in Bong County in central Liberia.
-
E.
The Ford
The Ford is a small hamlet within the civil parish of Little Hadham in Hertfordshire, England.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35958d49c8190b995188240fb355b |
completed | April 18, 2026, 10:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ee8812c81908ef74636bf39d44a |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:16 a.m.