Triple
T7665763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State (design pattern) |
E173619
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | State pattern |
E173619
|
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: State pattern | Statement: [State (design pattern), alsoKnownAs, State pattern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: State pattern Context triple: [State (design pattern), alsoKnownAs, State pattern]
-
A.
FSM
FSM is the three-letter ISO 3166-1 alpha-3 country code for the Federated States of Micronesia, a Pacific island nation.
-
B.
FSM
FSM is the abbreviation for the French Submarine Forces, the branch of the French Navy responsible for operating and maintaining France’s submarine fleet, including its nuclear deterrent.
-
C.
STATE
STATE is the commonly used abbreviation for the United States Department of State, the federal executive department responsible for U.S. foreign policy and international relations.
-
D.
State
chosen
State is a behavioral design pattern that lets an object alter its behavior when its internal state changes, making it appear as if the object has changed its class.
-
E.
State
State is an underground subway station in downtown Boston that serves as a major transfer point between the MBTA Blue and Orange Lines.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701bfb67c81908b416802eaf0faac |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b1fdccc8190a69b4745dc3b2347 |
completed | March 29, 2026, 3:23 a.m. |
Created at: March 27, 2026, 4 p.m.