Triple
T8248687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maltego |
E192903
|
entity |
| Predicate | offersEdition |
P15708
|
FINISHED |
| Object | Maltego XL |
E192903
|
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: Maltego XL | Statement: [Maltego, offersEdition, Maltego XL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maltego XL Context triple: [Maltego, offersEdition, Maltego XL]
-
A.
Maltego
chosen
Maltego is a graphical link analysis and data mining tool widely used in digital forensics and open-source intelligence (OSINT) investigations.
-
B.
Social-Engineer Toolkit
Social-Engineer Toolkit is an open-source penetration testing framework focused on automating and simulating social engineering attacks such as phishing, credential harvesting, and other human-targeted exploits.
-
C.
Tenable
Tenable is a British daytime television quiz show, hosted by Warwick Davis, in which teams of contestants attempt to complete top-ten lists on a variety of topics.
-
D.
Nessus
Nessus is a centaur in Greek mythology best known for his role in the death of Heracles after deceitfully causing the poisoned garment incident.
-
E.
Nessus
Nessus is a widely used vulnerability scanning tool that identifies security weaknesses in networks, systems, and applications.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c6b3c48190a3ecebf449766124 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc6b591d081909e1fb450508197f2 |
completed | April 2, 2026, 1:30 a.m. |
Created at: March 30, 2026, 5:48 p.m.