Triple
T1773941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MFS |
E38935
|
entity |
| Predicate | succeededBy |
P78
|
FINISHED |
| Object | HFS |
E200272
|
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: HFS | Statement: [MFS, succeededBy, HFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HFS Context triple: [MFS, succeededBy, HFS]
-
A.
HFS
chosen
HFS (Hierarchical File System) is a classic file system developed by Apple for early Macintosh computers, organizing data in a tree-structured hierarchy with support for resource forks and metadata.
-
B.
HES
HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
-
C.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
D.
HF
HF is the Faculty of Humanities at the University of Oslo, encompassing disciplines such as languages, history, culture, and philosophy.
-
E.
FFS
FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b59428819082e0d43a61f4f299 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c96694819085f3ccafb141802f |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:31 p.m.