Triple
T20633201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In-Home Supportive Services |
E507008
|
entity |
| Predicate | hasAcronym |
P43
|
FINISHED |
| Object | IHSS |
—
|
NE NERFINISHED |
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: IHSS | Statement: [In-Home Supportive Services, hasAcronym, IHSS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IHSS Context triple: [In-Home Supportive Services, hasAcronym, IHSS]
-
A.
IHSS
chosen
IHSS (In-Home Supportive Services) is a California program that provides in-home care to low-income seniors and people with disabilities so they can safely remain in their own homes.
-
B.
IHS
IHS is IBM's web server software based on the Apache HTTP Server, used to serve and manage web content in enterprise environments.
-
C.
IHS
IHS is a U.S. federal agency within the Department of Health and Human Services that provides health services to American Indians and Alaska Natives.
-
D.
HIP
HIP is a C++ runtime and programming model developed by AMD that enables portable GPU-accelerated code across AMD and NVIDIA hardware.
-
E.
HIP
HIP is the vehicle registration code for the German district of Roth in the state of Bavaria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad0d808c81908a60abd02a22ed92 |
completed | April 20, 2026, 10:47 p.m. |
Created at: April 16, 2026, 11:42 a.m.