Triple
T9838495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Symbolic Model Checking |
E239161
|
entity |
| Predicate | supportsLogic |
P15794
|
FINISHED |
| Object |
LTL
LTL (Linear Temporal Logic) is a formalism used in computer science and logic to specify and reason about the temporal ordering of events along linear time, particularly in the verification of reactive and concurrent systems.
|
E824076
|
NE FINISHED |
How this triple was built (4 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: LTL | Statement: [Symbolic Model Checking, supportsLogic, LTL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LTL Context triple: [Symbolic Model Checking, supportsLogic, LTL]
-
A.
LTL
LTL is the former official currency code for the Lithuanian litas, which was replaced by the euro in 2015.
-
B.
LTL
LTL is the National Rail station code for Littleborough railway station in Greater Manchester, England.
-
C.
TLT
TLT is the time zone abbreviation used for Timor Leste Time, the standard time observed in East Timor.
-
D.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
E.
Lt
Lt is the standard military abbreviation for the commissioned officer rank of Lieutenant in the Australian Army.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: LTL Triple: [Symbolic Model Checking, supportsLogic, LTL]
Generated description
LTL (Linear Temporal Logic) is a formalism used in computer science and logic to specify and reason about the temporal ordering of events along linear time, particularly in the verification of reactive and concurrent systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LTL Target entity description: LTL (Linear Temporal Logic) is a formalism used in computer science and logic to specify and reason about the temporal ordering of events along linear time, particularly in the verification of reactive and concurrent systems.
-
A.
LTL
LTL is the National Rail station code for Littleborough railway station in Greater Manchester, England.
-
B.
LTL
LTL is the former official currency code for the Lithuanian litas, which was replaced by the euro in 2015.
-
C.
TLT
TLT is the time zone abbreviation used for Timor Leste Time, the standard time observed in East Timor.
-
D.
TLA
TLA is a formal specification language developed by Leslie Lamport for describing and reasoning about concurrent and distributed systems using temporal logic.
-
E.
Lt
Lt is the standard military abbreviation for the commissioned officer rank of Lieutenant in the Australian Army.
- F. None of above. chosen
Provenance (5 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb34921b881909836ba0f5b42a27b |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5d145ac8190ad10a4328216ef54 |
completed | April 5, 2026, 3:24 a.m. |
| NEDg | Description generation | batch_69d1d6bb23cc81909efbeccf147018e8 |
completed | April 5, 2026, 3:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d726e58c819090135d1ff275d2d8 |
completed | April 5, 2026, 3:29 a.m. |
Created at: March 30, 2026, 8:33 p.m.